Systems, terminals, and programs

Abstract

The objective of the present invention is to provide a system, terminal, and program that can obtain trends in real estate information for each attribute of the property. [Solution] The present invention is a system comprising one or more computers. The storage device of one or more computers stores multiple real estate information related to real estate. The control device of one or more computers extracts one or more target real estate information from the multiple real estate information based on input information generated by user input processing, obtains classification condition information indicating one or more selected classification conditions from one or more classification conditions for classifying one or more target real estate information into one or more categories, classifies one or more target real estate information into one or more categories based on the classification condition information, and generates graph information showing a graph having one or more series corresponding to each of the one or more categories based on the one or more target real estate information.

Description

Technical Field

[0001] The present invention relates to a system, a terminal, and a program.

Background Art

[0002] As an invention related to a conventional system, for example, a profit evaluation device described in Patent Document 1 is known. In this system, the distribution analysis function generates rental distribution data, vacancy rate distribution data, and turnover rate distribution data indicating the turnover rate of rental contracts from rental housing recruitment data in a wide area including the location of the property to be evaluated and for a predetermined period going back in the past. The rental / vacancy rate calculation function extracts data corresponding to the property information and access information of the property to be evaluated from the rental distribution data and the vacancy rate distribution data, and calculates the rent and vacancy rate of the property to be evaluated. The operating income calculation function calculates the operating income according to the calculated rent and vacancy rate of the property to be evaluated. The operating expense calculation function extracts data corresponding to the property information from the turnover rate distribution data, and calculates the operating expenses of the property to be evaluated. The profit calculation function calculates the profit of the property to be evaluated from the operating income, the operating expenses, and the rate of return.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] By the way, real estate has attributes such as region and floor plan. The trends of real estate information such as rent of real estate have characteristics for each attribute. Therefore, users have a desire to know the trends of real estate information for each attribute of real estate.

[0005] Therefore, an object of the present invention is to provide a system, a terminal, and a program capable of obtaining the trends of real estate information for each attribute of real estate. [Means for solving the problem]

[0006] The first form is, A system comprising one or more computers, The storage devices of the aforementioned one or more computers store multiple pieces of real estate information related to real estate, The control devices of the one or more computers described above are: Based on the input information generated by the user's input processing, one or more target property information is extracted from the multiple property information, To classify the aforementioned one or more target real estate information into one or more categories, obtain classification condition information that indicates one or more selected classification conditions from one or more classification conditions, Based on the classification criteria information, the one or more target real estate information is classified into one or more categories. Based on the one or more target property information, graph information is generated showing a graph having one or more series corresponding to each of the one or more categories. It is a system.

[0007] The second form is, The user can select one or more desired classification criteria from among one or more classification criteria. The control devices of the one or more computers described above are: In the process of obtaining the classification condition information, the classification condition information is obtained that indicates one or more selected classification conditions selected by the user. This is the system described in the first form.

[0008] The third form is, The control devices of the one or more computers described above are: Obtain graphing condition information indicating the graphing conditions for generating the aforementioned graph, In the process of generating the graph information, graph information is generated that shows a graph having one or more series corresponding to each of the one or more categories, based on the one or more target property information and the graphing condition information. This is the system described in the first form.

[0009] The fourth form is, The control devices of the one or more computers described above are: In the process of generating I, one or more numerical values ​​used in the graph are calculated for each of the one or more categories based on one or more parameters included in the one or more target property information. This is the system described in the third form.

[0010] The fifth form is, The user can select the desired graphing conditions from several types of graphing conditions. The control devices of the one or more computers described above are: In the process of obtaining the graphing condition information, the graphing condition information corresponding to the graphing condition selected by the user is obtained. This is the system described in the third or fourth form.

[0011] The sixth form is, The graphing conditions mentioned above indicate the parameters used on the vertical axis and / or horizontal axis of the graph. This is a system described in any of the third to fifth forms.

[0012] The seventh form is, Each of the aforementioned multiple pieces of real estate information includes a relationship between the first parameter and time, The graph has a first axis which is the time axis and a second axis which shows the magnitude of the first parameter. The control devices of the one or more computers described above are: In the process of generating the graph information, the average value of the first parameter included in the one or more target property information belonging to the one or more categories is calculated as one or more numerical values ​​used in the graph. This is the system described in the fourth form.

[0013] The eighth form is, The first parameter is the rent of the real estate, the area of the real estate, or the number of recruitment cases of the real estate. The system according to the seventh aspect.

[0014] The ninth aspect is Each of the plurality of real estate information includes a first parameter and a second parameter. The graph has a first axis that is a time axis and a second axis that indicates the magnitude of the third parameter. The control device of the one or more computers is In the process of generating the graph information, a third parameter obtained based on the first parameter and the second parameter included in the one or more target real estate information belonging to the one or more categories is calculated as one or more numerical values used for the graph. The system according to any one of the first to third aspects.

[0015] The tenth aspect is The third parameter is the operating rate of the real estate, the vacancy rate of the real estate, or the per-square-meter price of the real estate. The system according to the ninth aspect.

[0016] The eleventh aspect is Each of the plurality of real estate information includes a first parameter and a second parameter. The graph has a first axis that indicates the magnitude of the first parameter and a second axis that indicates the magnitude of the second parameter. The control device of the one or more computers is In the process of generating the graph information, the first parameter included in the one or more target real estate information belonging to the one or more categories is calculated as one or more numerical values used for the graph, and the second parameter included in the one or more target real estate information belonging to the one or more categories is calculated as one or more numerical values used for the graph. The system according to any one of the first to third aspects.

[0017] The 12th form is, The aforementioned real estate information includes the address of the property, the distance from the property to the nearest station, the year the property was built, or the floor plan of the property. The system is one of the first to eleventh forms.

[0018] The 13th form is, The aforementioned input information indicates search conditions for extracting one or more target property information from the multiple property information. The system is one of the first to twelfth forms.

[0019] The 14th form is, The aforementioned input information indicates the property specified by the user, The control devices of the one or more computers described above are: In the process of extracting one or more target property information, property information related to the property specified by the user, and property information related to properties similar to the property specified by the user are extracted as one or more target property information. The system is one of the first to thirteenth forms.

[0020] The 15th form is, Each of the aforementioned multiple pieces of real estate information includes a first parameter and a second parameter, The control devices of the one or more computers described above are: In the process of generating the graph information, first graph information is generated showing a first graph having one or more series corresponding to each of the one or more categories, based on the first parameter included in the one or more target real estate information, and second graph information is generated showing a second graph having one or more series corresponding to each of the one or more categories, based on the second parameter included in the one or more target real estate information. The system is one of the first, second, or third forms described.

[0021] The 16th form is, The aforementioned one or more computers are equipped with machine learning models, The control devices of the one or more computers described above are: In the process of generating the graph information, by inputting the one or more target real estate information into the machine learning model, one or more second values ​​used in the graph are calculated for each of the one or more categories. The aforementioned second numerical value of 1 or more is a value that interpolates or extrapolates the aforementioned numerical value of 1 or more in the graph. This is a system described in any of the fourth to eleventh forms.

[0022] The 17th form is, The computer's storage device stores multiple pieces of real estate information related to real estate, The control unit of the aforementioned computer, Based on the input information generated by the user's input processing, one or more target property information is extracted from the multiple property information. To obtain classification condition information that indicates one or more selected classification conditions from one or more classification conditions for classifying the aforementioned one or more target real estate information into one or more categories, Based on the classification criteria information, the one or more target properties are classified into one or more categories. Based on the one or more target real estate information, graph information is generated showing a graph having one or more series corresponding to each of the one or more categories. It is a program.

[0023] The 18th form is, A terminal that is connected to a computer in a manner that enables communication, The storage device of the aforementioned computer stores multiple pieces of real estate information related to real estate, The control device of the aforementioned terminal is The input information is obtained through the user input process of the aforementioned terminal. By transmitting the aforementioned input information to the computer, the computer is made to extract one or more target property information from the multiple property information, The user input process obtains classification condition information indicating one or more selected classification conditions from one or more classification conditions for classifying the one or more target real estate information into one or more categories. By transmitting the classification condition information to the computer, the computer generates graph information showing a graph having one or more series. The aforementioned graph information is obtained from the computer, Based on the graph information, the graph is displayed on the terminal's display. The aforementioned one or more series correspond to each of the one or more categories into which the aforementioned one or more subject properties are classified based on the classification condition information. It is a terminal.

[0024] The 19th form is, A program that runs on a terminal that is connected to a computer in a communicative manner, The storage device of the aforementioned computer stores multiple pieces of real estate information related to real estate, The program is controlled by the terminal's control device. The terminal's user input process allows the input information to be obtained. By transmitting the aforementioned input information to the computer, the computer is made to extract one or more target property information from the multiple property information, The user input process obtains classification condition information indicating one or more selected classification conditions from one or more classification conditions for classifying the one or more target real estate information into one or more categories. By transmitting the classification condition information to the computer, graph information showing a graph having one or more series is generated. The aforementioned graph information is obtained from the computer. Based on the graph information, the graph is displayed on the terminal's display. The aforementioned one or more series correspond to each of the one or more categories into which the aforementioned one or more subject properties are classified based on the classification condition information. It is a program. [Effects of the Invention]

[0025] According to the present invention, trends in real estate information can be obtained for each attribute of the property. [Brief explanation of the drawing]

[0026] [Figure 1] Figure 1 is an explanatory diagram of System 1. [Figure 2] Figure 2 is a block diagram of user terminal 10. [Figure 3] Figure 3 is a block diagram of server 110. [Figure 4] Figure 4 shows a table of real estate information. [Figure 5] Figure 5 shows a table of recruitment information. [Figure 6] Figure 6 shows a tenant information table. [Figure 7] Figure 7 shows a table of land price information. [Figure 8] Figure 8 shows an image displayed on the display 20 of the user terminal 10. [Figure 9] Figure 9 is a flowchart showing the actions performed by the control device 12 of the user terminal 10 and the control device 112 of the server 110. [Figure 10] Figure 10 shows an image displayed on the display 20 of the user terminal 10. [Figure 11] Figure 11 shows an image displayed on the display 20 of the user terminal 10. [Figure 12] Figure 12 shows an image displayed on the display 20 of the user terminal 10. [Figure 13] Figure 13 shows an image displayed on the display 20 of the user terminal 10. [Figure 14] Figure 14 shows an image displayed on the display 20 of the user terminal 10. [Figure 15] Figure 15 shows an image displayed on the display 20 of the user terminal 10. [Modes for carrying out the invention]

[0027] (Embodiment) System 1 according to an embodiment of this disclosure will be described with reference to the drawings.

[0028] [System 1 Structure] First, the overall configuration of System 1 will be explained with reference to the diagrams. Figure 1 is an explanatory diagram of System 1. Figure 2 is a block diagram of the user terminal 10. Figure 3 is a block diagram of the server 110.

[0029] System 1, shown in Figure 1, comprises user terminals 10 (one or more computer terminals) and servers 110 (one or more computers). The user terminals 10 and servers 110 are connected to each other via a communication network. The network can be the internet, an intranet, or similar.

[0030] User terminal 10 is a computer. User terminal 10 is an information processing device used by user X. User terminal 10 is, for example, a smartphone, a tablet device, or a personal computer. As shown in Figure 2, user terminal 10 includes a control device 12, a storage device 14, a network interface 16, a graphics processing unit 18, a display 20, an operation unit 26, and a touch panel 28.

[0031] The storage device 14 stores the program PG2 and data. The storage device 14 is, for example, a combination of ROM (Read Only Memory), RAM (Random Access Memory), and storage (for example, flash memory or hard disk).

[0032] Program PG2 includes, for example, the following programs: • OS (Operating System) programs • Programs for applications that perform information processing (e.g., web browsers, or target applications described later)

[0033] 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)

[0034] The control device 12 implements the functions of the user terminal 10 by executing the program PG2 stored in the storage device 14. The control device 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)

[0035] The control device 12 includes, as functional blocks, an input information acquisition means 42, an input information transmission control means 44, a classification condition information acquisition means 46, a classification condition information transmission control means 48, a graph information acquisition means 50, and a display control means 52.

[0036] The network interface 16 controls communication between the user terminal 10 and an external device. The external device is a server 110.

[0037] The graphics processing unit 18 displays an image on the display 20 based on the image data generated by the control device 12. The display 20 is either a liquid crystal display or an organic EL (Electro-Luminescence) display.

[0038] The operation unit 26 generates an operation signal based on the user's operation via the touch panel 28 and outputs the operation signal to the control device 12.

[0039] System 1 may include multiple user terminals 10.

[0040] Server 110 is a computer. Server 110 is a web server that stores web page data. As shown in Figure 3, Server 110 includes a control unit 112, a storage device 114, and a network interface 116.

[0041] The storage device 114 stores the program PG1 and data. The storage device 114 is, for example, a combination of ROM (Read Only Memory), RAM (Random Access Memory), and storage (for example, flash memory or hard disk).

[0042] The control device 112 implements the functions of the server 110 by executing the program PG1 stored in the storage device 114. The control device 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)

[0043] The control device 112 includes, as functional blocks, a target real estate information extraction means 120, a classification condition information acquisition means 122, a category classification means 124, a graph information generation means 126, and a graphing condition information acquisition means 128.

[0044] The network interface 116 controls communication between the server 110 and an external device. The external device is a user terminal 10.

[0045] [Database] The databases stored in the storage device 114 of the server 110 will now be described. Figure 4 shows the real estate information table. Figure 5 shows the listing information table. Figure 6 shows the tenant information table. Figure 7 shows the land price information table.

[0046] As shown in Figure 3, the storage device 114 has a property information DB 114a, a recruitment information DB 114b, a tenant information DB 114c, and a land price information DB 114d. The property information DB 114a stores the property information table shown in Figure 4. The property information table contains multiple property information I1. Property information I1 describes detailed information about a building that has rooms available for rent. In this embodiment, property information I1 includes property ID, property name, address (address of the property), asset type, completion year, leased area, total floor area, ceiling height, floor load, number of rooms, nearest station, year built (year of construction of the property), standard floor area, distance from the nearest station (distance from the property to the nearest station), price per tsubo, rent, and latitude and longitude. Note that a separate property information table may be provided for each asset type.

[0047] The recruitment information DB114b stores the recruitment information table shown in Figure 5. The recruitment information table contains multiple recruitment information I2 entries. Recruitment information I2 entries describe detailed information about rooms that are being advertised for rent. Recruitment information I2 entries include the recruitment ID, property ID, leased portion, floor plan (floor plan of the property), leased portion area, recruitment price, first information acquisition date, and recruitment status. The control device 112 of the server 110 generates a new recruitment information I2 entry each time a room in the property is advertised for rent and records it in the recruitment information table shown in Figure 5. The first information acquisition date is the date on which recruitment information I2 was recorded in the recruitment information table. Therefore, there are as many recruitment information I2 entries for the same room as there have been times it has been advertised for rent. However, the recruitment IDs of the recruitment information I2 entries for the same room are different from each other.

[0048] The tenant information DB114c stores the tenant information table shown in Figure 6. The tenant information table contains multiple tenant information I3 entries. Tenant information I3 entries describe detailed information about the tenants occupying the property. Tenant information I3 entries include tenant ID, tenant name, property ID, tenant industry, number of employees, and tenancy period. Note that the tenancy period for rooms currently available for rent is left blank.

[0049] The land value information DB114d stores the land value information table shown in Figure 7. The land value information table contains multiple land value information I4. Land value information I4 describes information about the land value in each area. Land value information I4 includes area, route number, latitude and longitude, land value, and second information acquisition date.

[0050] In this specification, multiple property information I1, multiple listing information I2, multiple tenant information I3, and multiple land price information I4 are collectively referred to as multiple real estate information I10. Therefore, the storage device 114 of the server 110 (one or more computers) stores multiple real estate information I10 related to real estate. Furthermore, real estate is a general term for buildings (properties) and rooms.

[0051] [System 1 Operation] Next, the operation of System 1 will be explained with reference to the diagrams. Figure 8 shows an image displayed on the display 20 of the user terminal 10.

[0052] First, let's explain the operation overview of System 1. System 1 displays the graph image shown in Figure 8 on the user terminal 10. The graph image shown in Figure 8 includes graph display area A1 and property display area A2. Graph display area A1 includes the first graph 200. The first graph 200 includes a vertical axis 202 and a horizontal axis 204. In the first graph 200 of Figure 8, the parameter used for the vertical axis 202 is the price per tsubo (unit of area). The parameter used for the horizontal axis 204 is time. The first graph 200 shows the relationship between the price per tsubo and time in Chiyoda Ward, Tokyo.

[0053] Graph 1 200 has one or more series. Graph 1 200 shown in Figure 8 has five series K1 to K5. Series K1 shows the relationship between the price per tsubo (unit area) of a room with a 1-room layout and the time of day. Series K2 shows the relationship between the price per tsubo of a room with a 1K layout and the time of day. Series K3 shows the relationship between the price per tsubo of a room with a 1LDK layout and the time of day. Series K4 shows the relationship between the price per tsubo of a room with a 2LDK layout and the time of day. Series K5 shows the relationship between the price per tsubo of a room with a 3LDK layout and the time of day.

[0054] Furthermore, property display area A2 contains multiple property details I5. Property details I5 describe information about the properties referenced when generating the first graph information I16, which shows the first graph 200. The first graph information I16 shows the first graph 200, which has one or more series K1 to K5 corresponding to one or more categories. The first graph information I16 includes checkboxes 211. Information about properties with checkboxes 211 checked is reflected in the first graph 200.

[0055] In order to display the image shown in Figure 8 on the user terminal 10, the control device 12 of the user terminal 10 and the control device 112 of the server 110 execute the flowchart shown in Figure 9, as described below. Figure 9 is a flowchart executed by the control device 12 of the user terminal 10 and the control device 112 of the server 110. Figure 10 is a diagram showing the image displayed on the display 20 of the user terminal 10.

[0056] The control device 112 of the server 110 reads the program PG1 stored in the storage device 114, causing the control device 112 of the server 110 to execute the operations described below using the program PG1. The program PG1 causes the input information acquisition means 42, input information transmission control means 44, classification condition information acquisition means 46, classification condition information transmission control means 48, graph information acquisition means 50, and display control means 52 to execute.

[0057] The control device 12 of the user terminal 10 reads the program PG2 stored in the storage device 14, causing the program PG2 to execute the operations described below on the control device 12 of the user terminal 10. The program PG2 causes the target real estate information extraction means 120, the classification condition information acquisition means 122, the category classification means 124, the graph information generation means 126, and the graphing condition information acquisition means 128 to execute.

[0058] First, user X inputs input information I11 by operating the operation unit 26 of the user terminal 10 on a search screen (not shown). Input information I11 indicates search conditions for extracting one or more target real estate information I110 from multiple real estate information I10. Multiple real estate information I10 are multiple property information I1 (see property information table shown in Figure 4), multiple recruitment information I2 (see recruitment information table shown in Figure 5), multiple tenant information I3 (see tenant information table shown in Figure 6), and multiple land price information I4 (see land price information table shown in Figure 7) stored in the storage device 114 of the server 110. The search conditions are the conditions that user X is looking for in a room. The search conditions include, for example, address, floor plan, leased portion, leased portion area, etc. In this embodiment, the search conditions include the address. User X then inputs the search conditions by specifying Chiyoda-ku, Tokyo as the address.

[0059] The control device 12 (input information acquisition means 42) of the user terminal 10 acquires input information I11 through the input processing of user X of the user terminal 10 (step S1). Then, the control device 12 (input information transmission control means 44) of the user terminal 10 transmits the input information I11 to the server 110 via the network interface 16 (step S2), causing the server 110 (one or more computers) to extract one or more target real estate information I110 from the multiple real estate information I10. Accordingly, the network interface 116 of the server 110 receives the input information I11 and outputs the input information I11 to the control device 112. As a result, the control device 112 of the server 110 acquires the input information I11 (step S101).

[0060] Next, the control device 112 (target real estate information extraction means 120) of the server 110 extracts one or more target real estate information I110 from a plurality of real estate information I10 based on the input information I11 generated by the input processing of user X (step S102). More specifically, in the input information I11, Chiyoda-ku, Tokyo is specified as the address. Therefore, the control device 112 of the server 110 extracts one or more property information I1 that includes the address Chiyoda-ku, Tokyo from the property information table in Figure 4. The control device 112 of the server 110 extracts one or more recruitment information I2 and one or more tenant information I3 that include the property ID contained in the extracted one or more property information I1, respectively, from the recruitment information table in Figure 5 and the tenant information table in Figure 6. In this way, the control device 112 of the server 110 extracts one or more property information I1, one or more recruitment information I2, and one or more tenant information I3, which are one or more target real estate information I110.

[0061] Next, the control device 112 of the server 110 generates extracted result image information I12 for displaying the extracted result image shown in Figure 10, based on one or more target real estate information I110, which consists of one or more property information I1, one or more recruitment information I2, and one or more tenant information I3 (step S103). The extracted result image includes a graph display area A1 and a property display area A2, similar to the graph image shown in Figure 8. However, the graph display area A1 of the extracted result image does not include a graph. On the other hand, the property display area A2 includes multiple property details I5. The multiple property details I5 correspond to one or more target real estate information I110 (one or more property information I1, one or more recruitment information I2, and one or more tenant information I3) extracted by the control device 112 of the server 110 in step S102.

[0062] Next, the control device 112 of the server 110 transmits the extracted image information I12 to the user terminal 10 via the network interface 16 (step S104). Accordingly, the network interface 16 of the user terminal 10 receives the extracted image information I12 and outputs the extracted image information I12 to the control device 12. As a result, the control device 12 of the user terminal 10 acquires the extracted image information I12 (step S3). Then, based on the extracted image information I12, the control device 12 of the user terminal 10 displays the extracted image shown in Figure 10 on the display 20 (step S4).

[0063] User X can select one or more desired classification conditions from one or more classification conditions in the extraction result image shown in Figure 10. The classification conditions are conditions for classifying one or more target real estate information I110 into one or more categories. Therefore, the extraction result image shown in Figure 10 includes a classification selection unit 210. The classification selection unit 210 includes a plurality of buttons selected by User X in order to classify one or more target real estate information I110 (one or more property information I1, one or more listing information I2, and one or more tenant information I3) extracted by the control device 112 of the server 110 in step S102 into one or more categories. The classification selection unit 210 includes a "Overall" button, a "Floor Plan" button, a "Year Built" button, and a "Walking Distance from Station" button. User X can touch one of the "Overall" button, the "Floor Plan" button, the "Year Built" button, or the "Walking Distance from Station" button by operating the operation unit 26 of the user terminal 10. In this embodiment, User X touches the "Floor Plan" button. Accordingly, the control device 12 (classification condition information acquisition means 46) of the user terminal 10 acquires classification condition information I13, which indicates one or more selected classification conditions selected from the selection conditions for classifying one or more target real estate information I110 into one or more categories, through the input processing of user X (step S5). That is, the control device 12 of the user terminal 10 acquires classification condition information I13, which indicates one or more selected classification conditions selected by user X. In this embodiment, the classification condition information I13 indicates that one or more target real estate information I110 are classified into one or more categories based on their floor plan.

[0064] Next, the control device 12 (classification condition information transmission control means 48) of the user terminal 10 transmits classification condition information I13 to the server 110 (one or more computers) via the network interface 16 (step S6), causing the server 110 (one or more computers) to generate graph information I14 showing a first graph 200 having one or more series. Accordingly, the network interface 116 of the server 110 receives the classification condition information I13 and outputs the classification condition information I13 to the control device 112. As a result, the control device 112 (classification condition information acquisition means 122) of the server 110 acquires classification condition information I13 showing one or more selected classification conditions selected from one or more classification conditions for classifying one or more target real estate information I110 into one or more categories (step S105).

[0065] Next, the control device 112 (category classification means 124) of the server 110 classifies one or more target real estate information I110 (one or more property information I1, one or more listing information I2, and one or more tenant information I3) into one or more categories based on the classification condition information I13 (step S106). In this embodiment, the classification condition information I13 indicates that one or more target real estate information I110 are classified into one or more categories based on their floor plan. Therefore, the control device 112 of the server 110 refers to the floor plan of one or more listing information I2 included in the one or more target real estate information I110. Then, the control device 112 of the server 110 classifies the one or more target real estate information I110 into the categories of "1 room", "1K", "1LDK", "2LDK", and "3LDK".

[0066] By the way, user X can select the desired graphing conditions from several types of graphing conditions. The graphing conditions are the conditions for generating the first graph 200. Specifically, the graphing conditions indicate the parameters used for the vertical axis of the first graph 200. Therefore, the extracted result image shown in Figure 10 includes an axis selection unit 212. The axis selection unit 212 includes several buttons for user X to select the parameters used for the vertical axis 202 of the first graph 200. The axis selection unit 212 includes buttons for "price per tsubo", "total rent", "occupancy rate", and "number of units available". User X can touch any of the buttons for "price per tsubo", "total rent", "occupancy rate", and "number of units available" by operating the operation unit 26 of the user terminal 10. In this embodiment, user X touches the "price per tsubo" button. Accordingly, the control device 12 of the user terminal 10 acquires graphing condition information I15 indicating the graphing conditions for generating the first graph 200 (step S7). In this embodiment, the graphing condition information I15 indicates that the parameter used for the vertical axis 202 of the first graph 200 is the price per tsubo (unit of area).

[0067] Next, the control device 12 of the user terminal 10 transmits graphing condition information I15 to the server 110 (one or more computers) via the network interface 16 (step S8). Accordingly, the network interface 116 of the server 110 receives the graphing condition information I15 and outputs the graphing condition information I15 to the control device 112. As a result, the control device 112 of the server 110 (graphing condition information acquisition means 128) acquires graphing condition information I15 indicating the graphing conditions for generating the first graph 200 (step S107). In other words, the control device 112 of the server 110 acquires graphing condition information I15 corresponding to the graphing conditions selected by user X.

[0068] Next, the control device 112 (graph information generation means 126) of the server 110 generates first graph information I16 based on one or more target real estate information I110 (one or more property information I1, one or more recruitment information I2, and one or more tenant information I3) and graphing condition information I15 (step S108). The first graph information I16 shows a first graph 200 having one or more series K1 to K5 corresponding to one or more categories. Here, each of the multiple recruitment information I2 (multiple real estate information) includes an recruitment price (first parameter) and a leased area (second parameter). The control device 112 of the server 110 then calculates one or more numerical values ​​to be used in the first graph 200, based on the recruitment price (first parameter) and leased area (second parameter) included in one or more target real estate information I110 (one or more recruitment information I2) belonging to one or more categories, and uses these values ​​as the price per tsubo (third parameter).

[0069] More specifically, the control device 112 of server 110 arranges one or more listings I2 in chronological order based on the first information acquisition date of each listing I2. Then, the control device 112 of server 110 calculates the average unit price per tsubo for one or more listings I2 belonging to the same category and the same month and year. For example, the control device 112 of server 110 divides three times the listing price included in each of the one or more listings I2 belonging to the "1-room" category and January 2024 by the area of ​​the leased portion. In this way, the control device 112 of server 110 calculates the unit price per tsubo for each of the one or more listings I2 belonging to the "1-room" category and January 2024. The control device 112 of server 110 then calculates the sum of the unit prices per tsubo for the one or more listings I2 belonging to the "1-room" category and January 2024. The control device 112 of server 110 divides the total price per tsubo by the number of listings I2 belonging to the "1-room" category and January 2024. This allows the control device 112 of server 110 to calculate the average price per tsubo for the one or more listings I2 belonging to the "1-room" category and January 2024. Then, by repeating this process, the control device 112 of server 110 calculates the average price per tsubo for all categories and all months and years. This allows the control device 112 of server 110 to generate the first graph information I16. The first graph information I16 contains a large amount of coordinate data associated with the average price per tsubo, category, and month and year.

[0070] Next, the control device 112 of the server 110 transmits the first graph information I16 to the user terminal 10 via the network interface 16 (step S109). Accordingly, the network interface 16 of the user terminal 10 receives the first graph information I16 and outputs the first graph information I16 to the control device 12. As a result, the control device 12 (graph information acquisition means 50) of the user terminal 10 acquires the first graph information I16 from the server 110 (one or more computers) (step S9).

[0071] Next, the control device 12 (display control means 52) of the user terminal 10 displays the graph image shown in Figure 8 on the display 20 based on the first graph information I16 (step S10). More specifically, the graph image includes the first graph 200. The first graph 200 has a horizontal axis 204 (first axis) which is the time axis and a vertical axis 202 (second axis) which shows the magnitude of the price per tsubo (third parameter). The control device 12 of the user terminal 10 plots the numerous coordinate data included in the first graph information I16 onto the first graph 200. Then, the control device 12 of the user terminal 10 connects multiple coordinate data belonging to the same category with straight lines. This generates the series K1 to K5. After this, this process ends.

[0072] [Other examples of graph images] Other examples of graph images are described below with reference to the diagrams. Figures 11 to 13 show images displayed on the display 20 of the user terminal 10.

[0073] The control device 12 of the user terminal 10 may display the graph image shown in Figure 11 on the display 20. The graph image shown in Figure 11 includes the first graph 200. The first graph 200 includes a vertical axis 202 and a horizontal axis 204. In the first graph 200 of Figure 11, the parameter used for the vertical axis 202 is the occupancy rate. The parameter used for the horizontal axis 204 is time. The first graph 200 shows the relationship between the occupancy rate and time in Chiyoda Ward, Tokyo. The occupancy rate is the value obtained by dividing the number of rented rooms by the total number of rooms and multiplying by 100.

[0074] The first graph 200 has one or more series. The first graph 200 shown in Figure 11 has five series K11 to K15. Series K11 shows the relationship between the occupancy rate and time for properties that are 6 to 10 years old. Series K12 shows the relationship between the occupancy rate and time for properties that are 0 to 5 years old. Series K13 shows the relationship between the occupancy rate and time for properties that are 11 to 15 years old. Series K14 shows the relationship between the occupancy rate and time for properties that are 16 to 20 years old. Series K15 shows the relationship between the occupancy rate and time for properties that are 21 years old or older. Below, the process by which the control device 112 of the server 110 generates graph image information for displaying the graph image shown in Figure 11 will be explained using the flowchart shown in Figure 9. Steps S1-S4, S9, S10, S101-S104, and S109 in the process of generating graph image information for displaying the graph image shown in Figure 11 are the same as steps S1-S4, S9, S10, S101-S104, and S109 in the process of generating graph image information for displaying the graph image shown in Figure 8, so their explanation is omitted.

[0075] User X can select a desired classification criterion from one or more classification conditions in the extraction result image shown in Figure 10. The classification criterion is a condition for classifying one or more target real estate information I110 into one or more categories. Therefore, the extraction result image shown in Figure 10 includes a classification selection unit 210. The classification selection unit 210 includes multiple buttons that can be selected by User X in order to classify one or more target real estate information I110 (one or more property information I1, one or more listing information I2, and one or more tenant information I3) extracted by the control device 112 of the server 110 in step S102 into one or more categories. The classification selection unit 210 includes buttons for "Overall", "Floor Plan", "Year Built", and "Walking Distance from Station". User X can touch one of the buttons for "Overall", "Floor Plan", "Year Built", or "Walking Distance from Station" by operating the operation unit 26 of the user terminal 10. Therefore, User X touches the "Year Built" button. Accordingly, the control device 12 of the user terminal 10 obtains classification condition information I13, which indicates one or more selected classification conditions selected from one or more classification conditions for classifying one or more target real estate information I110 into one or more categories, through the input processing of user X (step S5). In this embodiment, the classification condition information I13 indicates that one or more target real estate information I110 are classified into one or more categories based on the year of construction.

[0076] Next, the control device 12 of the user terminal 10 transmits classification condition information I13 to the server 110 (one or more computers) via the network interface 16 (step S6), causing the server 110 (one or more computers) to generate graph information I14 showing a first graph 200 having one or more series. Accordingly, the network interface 116 of the server 110 receives the classification condition information I13 and outputs the classification condition information I13 to the control device 112. As a result, the control device 112 of the server 110 obtains classification condition information I13 showing one or more selected classification conditions selected from one or more classification conditions for classifying one or more target real estate information I110 into one or more categories (step S105).

[0077] Next, the control device 112 of the server 110 classifies one or more target real estate information I110 (one or more property information I1, one or more recruitment information I2, and one or more tenant information I3) into one or more categories based on the classification condition information I13 (step S106). In this embodiment, the classification condition information I13 indicates that one or more target real estate information I110 are classified into one or more categories based on the year of construction. Therefore, the control device 112 of the server 110 refers to the year of construction of one or more property information I1 included in the one or more target real estate information I110. Then, the control device 112 of the server 110 classifies the one or more property information I1 into categories of 0 to 5 years, 6 to 10 years, 11 to 15 years, 16 to 20 years, and 21 years or older. Furthermore, the control device 112 of the server 110 classifies the recruitment information I2 and tenant information I3, which include the property ID of the one or more property information I1 classified into the 0 to 5 year category, into the 0 to 5 year category. The control device 112 of server 110 classifies recruitment information I2 and tenant information I3 that include the property ID of one or more property information I1 classified into the 6-10 year category into the 6-10 year category. The control device 112 of server 110 classifies recruitment information I2 and tenant information I3 that include the property ID of one or more property information I1 classified into the 11-15 year category into the 11-15 year category. The control device 112 of server 110 classifies recruitment information I2 and tenant information I3 that include the property ID of one or more property information I1 classified into the 16-20 year category into the 16-20 year category. The control device 112 of server 110 classifies recruitment information I2 and tenant information I3 that include the property ID of one or more property information I1 classified into the 21 year or older category into the 21 year or older category.

[0078] By the way, user X can select the desired graphing conditions from several types of graphing conditions. The graphing conditions are the conditions for generating the first graph 200. Specifically, the graphing conditions indicate the parameters used for the vertical axis of the first graph 200. Therefore, the extracted result image shown in Figure 10 includes an axis selection unit 212. The axis selection unit 212 includes several buttons for user X to select the parameters used for the vertical axis 202 of the first graph 200. The axis selection unit 212 includes buttons for "price per tsubo", "total rent", "occupancy rate", and "number of units available". User X can touch any of the buttons for "price per tsubo", "total rent", "occupancy rate", and "number of units available" by operating the operation unit 26 of the user terminal 10. In this embodiment, user X touches the "occupancy rate" button. Accordingly, the control device 12 of the user terminal 10 acquires graphing condition information I15 indicating the graphing conditions for generating the first graph 200 (step S7). In this embodiment, the graphing condition information I15 indicates that the parameter used for the vertical axis 202 of the first graph 200 is the utilization rate.

[0079] Next, the control device 12 of the user terminal 10 transmits graphing condition information I15 to the server 110 (one or more computers) via the network interface 16 (step S8). Accordingly, the network interface 116 of the server 110 receives the graphing condition information I15 and outputs the graphing condition information I15 to the control device 112. As a result, the control device 112 of the server 110 obtains the graphing condition information I15 which indicates the graphing conditions for generating the first graph 200 (step S107). In other words, the control device 112 of the server 110 obtains the graphing condition information I15 which corresponds to the graphing conditions selected by user X.

[0080] Next, the control device 112 of the server 110 generates first graph information I16 showing a first graph 200 having one or more series K11 to K15 corresponding to one or more categories, based on one or more target real estate information I110 (one or more property information I1, one or more listing information I2, and one or more tenant information I3) and graphing condition information I15 (step S108). Here, each of the multiple property information I1 (multiple real estate information) includes the number of rooms (first parameter). The number of listing information I2 (multiple real estate information) that are currently being advertised is the number of vacant rooms (second parameter). The control device 112 of the server 110 then calculates the occupancy rate (third parameter) obtained based on the number of rooms (first parameter) included in one or more target real estate information I110 (one or more property information I1) belonging to one or more categories and the number of vacant rooms (second parameter) included in one or more target real estate information I110 (one or more listing information I2) belonging to one or more categories, as one or more numerical values ​​to be used in the first graph 200.

[0081] First, the control device 112 of server 110 arranges one or more listing information I2 in chronological order based on the first information acquisition date of one or more listing information I2. Then, the control device 112 of server 110 divides the number of listing information I2 (number of vacancies) belonging to the same category and the same year and month by the total number of rooms in one or more property information I1, which is one or more target real estate information I110. The control device 112 of server 110 calculates the occupancy rate by subtracting the value obtained by the division from 1 and multiplying by 100. The control device 112 of server 110 then calculates the occupancy rate for all categories and all years and months by repeating the same process. As a result, the control device 112 of server 110 generates the first graph information I16. Therefore, the first graph information I16 contains a large amount of coordinate data associated with the average price per tsubo, category, and year and month.

[0082] In Graph 1, 200, one or more target property information I110 are classified into one or more categories based on the year of construction. However, in Graph 1, 200 may also classify one or more target property information I110 into one or more categories based on distance from the station, town area, or municipality.

[0083] Furthermore, the control device 12 of the user terminal 10 may display the graph image shown in Figure 12 on the display 20. The graph image shown in Figure 12 includes the first graph 200. The first graph 200 includes a vertical axis 202 and a horizontal axis 204. In the first graph 200 of Figure 12, the parameter used for the vertical axis 202 is the number of units available for rent. The parameter used for the horizontal axis 204 is time. The first graph 200 may also show the relationship between the number of units available for rent and time in Chiyoda Ward, Tokyo. Note that in the first graph 200, one or more target real estate information I110 are not classified into one or more categories. However, in the first graph 200, one or more target real estate information I110 may be classified into one or more categories based on the year of construction, floor plan, and price per tsubo.

[0084] Furthermore, the control device 12 of the user terminal 10 may display the graph image shown in Figure 13 on the display 20. The graph image shown in Figure 13 includes the first graph 200. The first graph 200 includes a vertical axis 202 and a horizontal axis 204. In the first graph 200 of Figure 13, the parameter used for the vertical axis 202 is the vacancy rate. The vacancy rate is the value obtained by dividing the total area of ​​rooms currently being offered (the sum of the leased area of ​​rooms that are being offered to tenants) by the total area of ​​all rooms (the sum of the total floor area of ​​all properties) and multiplying by 100. The parameter used for the horizontal axis 204 is time. The first graph 200 may also show the relationship between the vacancy rate and time in Chiyoda Ward, Tokyo. In the first graph 200, one or more target real estate information I110 are classified into one or more categories based on the standard floor area. Therefore, the first graph 200 has series K51 to K54. However, in Graph 1, 200, one or more subject property information I110 may be classified into one or more categories based on the year of completion and rent range.

[0085] [effect] According to System 1, the trends of real estate information I10 can be obtained for each attribute of the room (real estate). More specifically, the control device 112 of Server 110 obtains classification condition information I13, which shows one or more selected classification conditions selected from one or more classification conditions for classifying one or more target real estate information I110 into one or more categories. As a result, the control device 112 of Server 110 can classify one or more target real estate information I110 into one or more categories based on the classification condition information I13. Through this classification process, one or more target real estate information I110 are classified into one or more categories according to the attributes of one or more target real estate information I110. Furthermore, the control device 112 of Server 110 can generate first graph information I16, which shows first graph 200 having series K1 to K5 corresponding to each of the one or more categories based on one or more target real estate information I110. Series K1 to K5 represent the trends of one or more target real estate information I110 for each attribute of the room (real estate). According to System 1, this allows us to obtain trends in real estate information I10 for each attribute of the room (property).

[0086] In System 1, User X can select one or more desired classification conditions from one or more classification conditions. The control device 112 of Server 110 then acquires classification condition information I13 indicating the one or more selected classification conditions by User X. As a result, User X can view the first graph 200 generated by the desired one or more selected classification conditions.

[0087] In System 1, User X can select a desired graphing condition from several types of graphing conditions. The control device 112 of Server 110 then acquires graphing condition information I15 corresponding to the graphing condition selected by User X. Based on this, the control device 112 of Server 110 can generate first graph information I16 showing a first graph 200 having series K1 to K5 corresponding to each of several categories, based on one or more target real estate information I110 and graphing condition information I15. As a result, User X can view the first graph 200 generated with the desired graphing condition. In this embodiment, the graphing condition indicates the parameters used for the vertical axis 202 of the first graph 200. Therefore, User X can view the first graph 200 having the desired vertical axis 202.

[0088] System 1 can obtain a first graph 200 that uses parameters not included in the real estate information I10. More specifically, each of the multiple real estate information I10 includes an asking price (first parameter) and a leased area (second parameter). Therefore, the control device 112 of server 110 calculates a price per tsubo (third parameter) obtained based on the asking price (first parameter) and leased area (second parameter) included in one or more target real estate information I110 belonging to one or more categories, and uses one or more numerical values ​​for the first graph 200. In this way, the control device 112 of server 110 calculates a price per tsubo (third parameter) not included in the target real estate information I110 based on the asking price (first parameter) and leased area (second parameter). As a result, System 1 can obtain a first graph 200 that uses parameters not included in the real estate information I10.

[0089] (First variation) Next, the system 1a relating to the first modified example will be described with reference to the drawings. Figure 14 shows an image displayed on the display 20 of the user terminal 10.

[0090] System 1a differs from System 1 in that the graph image shown in Figure 14 includes the first graph 200 and the second graph 300. These differences will be explained below with reference to the drawings.

[0091] Graph 1, 200, includes a vertical axis 202 and a horizontal axis 204. In Graph 1, 200, Figure 14, the parameter used for the vertical axis 202 is the vacancy rate. The parameter used for the horizontal axis 204 is time. Graph 1, 200, shows the relationship between the vacancy rate and time in Chiyoda Ward, Tokyo, and the relationship between the vacancy rate and time in Shibuya Ward, Tokyo.

[0092] Graph 1, 200, has one or more series. Graph 1, 200, shown in Figure 14, has two series, K21 and K22. Series K21 shows the relationship between vacancy rate and time in Chiyoda Ward, Tokyo. Series K22 shows the relationship between vacancy rate and time in Shibuya Ward, Tokyo.

[0093] In step S108, the control device 112 of the server 110 generates first graph information I16 showing a first graph 200 having one or more series K21, K22 corresponding to one or more categories, based on the number of units for sale (first parameter) included in one or more target real estate information I110. The number of units for sale is the number of currently available listings I2 included in one or more target real estate information I110.

[0094] Graph 300, the second graph, includes a vertical axis 302 and a horizontal axis 304. In Graph 300 of Figure 14, the parameter used for the vertical axis 302 is the available area stock. The available area stock is the total area of ​​rooms currently available for rent. The parameter used for the horizontal axis 304 is time. Graph 300 shows the relationship between the available area stock and time in Chiyoda Ward, Tokyo, and the relationship between the available area stock and time in Shibuya Ward, Tokyo.

[0095] The second graph 300 has one or more series. The second graph 300 shown in Figure 14 has two series K31 and K32. Series K31 shows the relationship between the available area stock and time in Chiyoda Ward, Tokyo. Series K32 shows the relationship between the available area stock and time in Shibuya Ward, Tokyo.

[0096] In step S108, the control device 112 of server 110 generates second graph information I26 showing a second graph 300 having one or more series K31, K32 corresponding to one or more categories, based on the leased area (second parameter) included in one or more target property information I110. The control device 112 of server 110 calculates the available area stock by calculating the sum of the leased area. The other configurations of system 1a are the same as those of system 1, so their explanation is omitted. System 1a can achieve the same effects as system 1.

[0097] According to system 1a, the control device 112 of server 110 generates first graph information I16 and second graph information I26. Therefore, the control device 12 of user terminal 10 can display a graph image including first graph 200 and second graph 300 based on the first graph information I16 and second graph information I26. This allows user X to view multiple graphs simultaneously. Thus, user X can conduct a more detailed examination of room rental by comparing the first graph 200 and the second graph 300.

[0098] (Second variation) Next, we will describe system 1b, which relates to the second modified example, with reference to the drawings. Figure 15 shows an image displayed on the display 20 of the user terminal 10.

[0099] System 1b differs from System 1 in that Graph 200 1 includes information for each property. These differences will be explained below with reference to the diagrams.

[0100] The first graph 200 shown in Figure 15 includes a vertical axis 202 and a horizontal axis 204. In the first graph 200 of Figure 15, the parameter used for the vertical axis 202 is the price per tsubo (a unit of area). The parameter used for the horizontal axis 204 is time. The first graph 200 shows the relationship between the price per tsubo and time. In the first graph 200, one or more target real estate information I110 are classified into one or more categories. Specifically, series K41 shows the relationship between the price per tsubo of Building A and time. Series K42 shows the relationship between the average price per tsubo of properties competing with Building A and time. Series K43 shows the relationship between the price per tsubo and time in Chiyoda Ward, Tokyo.

[0101] First, user X inputs input information I11 by operating the operation unit 26 of the user terminal 10 on a search screen (not shown). Input information I11 indicates search conditions for extracting one or more target real estate information I110 from multiple real estate information I10. User X inputs the search conditions by specifying Building A. Therefore, input information I11 indicates Building A (property / real estate) specified by user X.

[0102] The control device 12 of the user terminal 10 acquires input information I11 through the input processing of user X of the user terminal 10 (step S1). Then, the control device 12 of the user terminal 10 transmits the input information I11 to the server 110 via the network interface 16 (step S2), causing the server 110 (one or more computers) to extract one or more target real estate information I110 from the multiple real estate information I10. Accordingly, the network interface 116 of the server 110 receives the input information I11 and outputs the input information I11 to the control device 112. As a result, the control device 112 of the server 110 acquires the input information I11 (step S101).

[0103] Next, the control device 112 of the server 110 extracts one or more target real estate information I110, which includes real estate information I10 related to Building A (real estate) specified by user X, and real estate information I10 related to properties (real estate) similar to Building A (real estate) specified by user X (step S102). More specifically, Building A is specified in the input information I11. Therefore, the control device 112 of the server 110 extracts property information I1 for Building A, property information I1 for properties (real estate) similar to Building A, and one or more property information I1 whose address includes Chiyoda-ku, Tokyo, from the property information table in Figure 4. Property information I1 for properties (real estate) similar to Building A is property information I1 that includes a total floor area close to the total floor area of ​​Building A. One or more property information I1 whose address includes Chiyoda-ku, Tokyo, is one or more property information I1 related to properties located near Building A. The control device 112 of the server 110 extracts one or more recruitment information I2 from the recruitment information table in Figure 5 that contains the property ID included in one or more extracted property information I1. As a result, the control device 112 of the server 110 extracts one or more property information I1 and one or more recruitment information I2, which are one or more target real estate information I110.

[0104] Next, the control device 112 of the server 110 generates extracted result image information I12 for displaying the extracted result image shown in Figure 10, based on one or more target real estate information I110, which consists of one or more property information I1 and one or more listing information I2 (step S103). The extracted result image includes a graph display area A1 and a property display area A2, similar to the graph image shown in Figure 8. However, the graph display area A1 of the extracted result image does not include a graph. On the other hand, the property display area A2 includes multiple property details I5. The multiple property details I5 correspond to one or more target real estate information (one or more property information I1 and one or more listing information I2) extracted by the control device 112 of the server 110 in step S102.

[0105] Next, the control device 112 of the server 110 transmits the extracted image information I12 to the user terminal 10 via the network interface 16 (step S104). Accordingly, the network interface 16 of the user terminal 10 receives the extracted image information I12 and outputs the extracted image information I12 to the control device 12. As a result, the control device 12 of the user terminal 10 acquires the extracted image information I12. Then, based on the extracted image information I12, the control device 12 of the user terminal 10 displays the extracted image shown in Figure 10 on the display 20 (step S3).

[0106] User X can select one or more desired classification conditions from among one or more classification conditions in the extraction result image shown in Figure 10. Classification conditions are conditions for classifying one or more target real estate information I110 into one or more categories. In this case, in the extraction result image shown in Figure 10, User X selects Building A as the category for series K41, competing properties as the category for series K42, and Chiyoda-ku, Tokyo as the category for series K43. Accordingly, the control device 12 of the user terminal 10 acquires classification condition information I13, which indicates one or more selected classification conditions from among the classification conditions for classifying one or more target real estate information I110 into one or more categories, through User X's input processing (step S5). That is, the control device 12 of the user terminal 10 acquires classification condition information I13, which indicates one or more selected classification conditions selected by User X.

[0107] Next, the control device 12 of the user terminal 10 transmits classification condition information I13 to the server 110 (one or more computers) via the network interface 16 (step S6), causing the server 110 (one or more computers) to generate graph information I14 showing a first graph 200 having one or more series. Accordingly, the network interface 116 of the server 110 receives the classification condition information I13 and outputs the classification condition information I13 to the control device 112. As a result, the control device 112 of the server 110 obtains classification condition information I13 showing one or more selected classification conditions selected from one or more classification conditions for classifying one or more target real estate information I110 into one or more categories (step S105).

[0108] Next, the control device 112 of the server 110 classifies one or more target real estate information I110 (one or more property information I1, one or more listing information I2, and one or more tenant information I3) into one or more categories based on the classification condition information I13 (step S106). Then, the control device 112 of the server 110 refers to the property name of one or more listing information I2 included in the one or more target real estate information I110. Then, the control device 112 of the server 110 classifies one or more target real estate information I110 (one or more property information I1, one or more listing information I2, and one or more tenant information I3) that includes the property name of Building A into the category "Building A". The control device 112 of the server 110 refers to the address and total floor area of ​​one or more listing information I2 included in the one or more target real estate information I110. Then, the control device 112 of server 110 classifies one or more target real estate information I110 (one or more property information I1 and one or more listing information I2) that includes an address close to the address of Building A and a total floor area close to the total floor area of ​​Building A into the category of "competing properties". The control device 112 of server 110 refers to the address of one or more listing information I2 included in the one or more target real estate information I110. Then, the control device 112 of server 110 classifies one or more target real estate information I110 (one or more property information I1, one or more listing information I2 and one or more tenant information I3) that includes Chiyoda-ku, Tokyo as its address into the category of "Chiyoda-ku, Tokyo". The processing performed in system 1b after this is the same as in system 1, so the explanation is omitted. System 1b can achieve the same effect as system 1.

[0109] In system 1b, the control device 112 of server 110 extracts one or more target real estate information I110 from real estate information I10 related to the property (real estate) specified by user X, and real estate information I10 related to properties (real estate) similar to the property (real estate) specified by user X. As a result, the control device 112 of server 110 can generate first graph information I16 based on the real estate information I10 related to the property (real estate) specified by user X and the real estate information I10 related to properties (real estate) similar to the property (real estate) specified by user X. Consequently, the control device 12 of user terminal 10 can display the first graph 200 relating to the property specified by user X and properties similar to the property specified by user X on the display 20. Therefore, user X can compare the property specified by user X with properties similar to the property specified by user X.

[0110] (Third variation) Next, we will describe system 1c related to the third modified example.

[0111] System 1c differs from System 1 in that the parameter used for the horizontal axis of Graph 1 200 is not time. This difference will be explained below with reference to the diagram.

[0112] In System 1c, Graph 200 includes a vertical axis 202 and a horizontal axis 204. In Graph 200, the parameter used for the vertical axis 202 is the price per tsubo (a unit of area). The parameter used for the horizontal axis 204 is the leased area. Circles are also plotted in Graph 200. The size of the circles indicates the number of units available for lease. Graph 200 shows the relationship between the price per tsubo, the leased area, and the number of units available for lease. The other components of System 1c are the same as those of System 1, so their explanation is omitted. System 1c can achieve the same effect as System 1.

[0113] (Other embodiments) The system according to the present invention is not limited to systems 1, 1a to 1c, but can be modified within the scope of its gist.

[0114] Note that in systems 1,1a to 1c, graphing condition information I15 is not mandatory. Therefore, the control device 112 of the server 110 may generate first graph information I16 showing a first graph 200 having one or more series corresponding to one or more categories, based on one or more target real estate information I110. In other words, the first parameter used for the vertical axis and the second parameter used for the horizontal axis may be predetermined rather than selected by user X.

[0115] In addition, in systems 1,1a to 1c, the classification condition information I13 may be pre-stored in the storage device 114 of the server 110.

[0116] In systems 1,1a to 1c, the control device 112 of server 110 used a third parameter calculated from the first and second parameters included in property information I1 as the vertical axis (second axis). However, the vertical axis (second axis) may also represent the magnitude of the first parameter included in property information I1. In this case, each of the multiple real estate information I10 (multiple listing information I2) includes a relationship between the first parameter (e.g., listing price) and time. The first graph 200 has a horizontal axis (first axis) which is the time axis and a vertical axis (second axis) which shows the magnitude of the first parameter (listing price). The control device 112 of server 110 (one or more computers) may calculate one or more numerical values ​​used in the first graph 200 for one or more categories based on one or more first parameters (e.g., listing prices) included in one or more target real estate information I110. For example, the control device 112 of the server 110 (one or more computers) may calculate the average value of the first parameter (asking price) included in one or more target real estate information I110 belonging to one or more categories as one or more numerical values ​​used in the first graph 200. The first parameter may be the asking price of a room (rent of the property), the leased area of ​​the room (area of ​​the property), the number of rooms (property) being advertised, the occupancy rate of the property, the vacancy rate of the property, or the price per tsubo (unit of area) of the property.

[0117] In systems 1,1a to 1c, the first graph 200 has a vertical axis 202 (first axis) showing the magnitude of the first parameter (e.g., price per tsubo) and a horizontal axis 204 (second axis) showing time. However, the first graph 200 may also have a vertical axis 202 (first axis) showing the magnitude of the first parameter (e.g., asking price) and a horizontal axis 204 (second axis) showing the second parameter (e.g., leased area). In this case, each of the multiple real estate information I10 (multiple property information I1 and multiple listing information I2) includes a first parameter (e.g., asking price) and a second parameter (e.g., leased area). Then, the control device 112 of the server 110 (one or more computers) calculates a first parameter (e.g., asking price) included in one or more target real estate information I110 belonging to one or more categories as one or more numerical values ​​used in the first graph 200, and also calculates a second parameter (e.g., leased area) included in one or more target real estate information I110 belonging to one or more categories as one or more numerical values ​​used in the graph.

[0118] The server 110 may also be equipped with a machine learning model. More specifically, the number of coordinate data points in series K1 is less than the number of coordinate data points in series K2 or series K5. Therefore, the control device 112 of the server 110 may interpolate or extrapolate data by generating new coordinate data points for series K1 based on existing coordinate data points for series K1 using a machine learning model. More specifically, the control device 112 of the server 110 (one or more computers) inputs one or more target real estate information points I110 into a machine learning model to calculate one or more second numerical values ​​used in the first graph 200 for one or more categories. One or more second numerical values ​​are values ​​that interpolate or extrapolate one or more numerical values ​​in the graph.

[0119] In System 1, the control device 112 of Server 110 calculates the price per tsubo (third parameter - price per tsubo of real estate) obtained based on the asking price (first parameter) and leased area (second parameter) included in one or more target real estate information I110 (one or more listing information I2) belonging to one or more categories, and uses one or more numerical values ​​for use in Graph 1 200. However, the control device 112 of Server 110 may also calculate the room occupancy rate (real estate occupancy rate) or the room vacancy rate (real estate vacancy rate) as one or more numerical values ​​for use in Graph 1 200.

[0120] The control device 112 of the server 110 performs the processing in steps S106 to S108 each time a request is received from the user terminal 10. However, the control device 112 of the server 110 may store the results of the previously performed processing in steps S106 to S108 in the storage device 114. Then, if a request from the user terminal 10 is resent, the control device 112 of the server 110 may read the results from the storage device 114.

[0121] In addition, in systems 1,1a to 1f, the control device 112 of server 110 may calculate the median value of the parameters instead of the average value of the parameters.

[0122] In systems 1,1a to 1f, the control device 112 of server 110 may exclude outliers from the calculation of the average parameter value. Furthermore, the control device 112 of server 110 may exclude the largest and smallest parameters from the calculation of the average parameter value. In this case, when generating the first graph information I16, the control device 112 of server 110 does not need to include the property information I110 of the excluded parameters in the first graph information I16. As a result, the graph image will not include the property information I110 of the excluded parameters.

[0123] In System 1, if User X touches Series K1 by operating the operation unit 26 of User Terminal 10, the control device 12 of User Terminal 10 may display the property display area A2, which includes multiple property details I5 belonging to Series K1, on the display 20.

[0124] In System 1, when User X touches a button included in the classification selection unit 210 by operating the operation unit 26 of the user terminal 10, the user terminal 10 transmits new classification condition information I13 to the server 110. In this case, the control device 112 of the server 110 generates new first graph information I16 based on the classification condition information I13. That is, when User X presses a button included in the classification selection unit 210, the series of the first graph 200 changes.

[0125] In System 1, when User X touches a button included in the axis selection unit 212 by operating the operation unit 26 of the user terminal 10, the user terminal 10 transmits new graphing condition information I15 to the server 110. In this case, the control device 112 of the server 110 generates new first graph information I16 based on the graphing condition information I15. That is, when User X presses a button included in the classification selection unit 210, the vertical axis of the first graph 200 changes.

[0126] In System 1, the graph image shown in Figure 8 may include a map of Chiyoda Ward, Tokyo. In this case, an icon is placed at the location of each of the multiple rooms currently available for rent. The icons belonging to series K1, K2, K3, K4, and K5 may have different colors, shapes, etc., so that they can be distinguished from each other.

[0127] Furthermore, when generating the first graph information I16, the control device 112 of the server 110 may use a machine learning model to predict other results based on previously calculated results. Specifically, when generating the first graph information I16, the control device 112 of the server 110 may use a machine learning model to predict the result for Shibuya Ward, Tokyo, based on the result for Chiyoda Ward, Tokyo.

[0128] The control device 112 of the server 110 may generate the first graph information I16 using an address similar to the address specified by user X as a search condition.

[0129] Furthermore, the control device 112 of the server 110 may analyze the contents of the first graph information I16 using a generating AI based on the first graph information I16. In this case, the control device 112 of the server 110 may generate analysis result information such as, for example, analysis results predicting the peak period for the price per tsubo (unit of area), or analysis results analyzing trends in asking prices across regions. The control device 112 of the server 110 may also use the generating AI to generate analysis result information such as advice on whether the listed room is a good deal or not. For example, the control device 112 of the server 110 receives a prompt that includes the first graph information I16 or the data used to generate the first graph information I16, a generating AI (e.g., a Transformer model such as GPT), and a command statement corresponding to the analysis target selected by the user (e.g., predicting the peak period for the price per tsubo, trends in asking prices across regions, creating a graph summary, etc.), and outputs analysis result information based on the results output from the generating AI. This allows users to read the graph analysis results even if they do not have expertise in real estate.

[0130] Furthermore, the control device 112 of the server 110 may input a prompt to the generating AI that includes the first graph information I16 or the first graph information I16 and an analysis command, and output the analysis result based on the result output from the generating AI as analysis result information. The generating AI is a Transformer model such as GPT. The generating AI may be provided by the server 110 or by an external server. Examples of analysis commands include predicting the peak period for the price per tsubo from the input data, describing the trend of asking prices between regions from the input data, and creating a summary of the input graph. This allows users to read the analysis results of the graph and obtain explanations of the graph even if they do not have expertise in real estate. In this case, the analysis command may be input by the user, or the user may select and determine it from a set of predetermined commands. Furthermore, the control device 112 of the server 110 may display the first graph information I16 and an analysis generation object requesting analysis of the first graph information I16 to the user. If the user selects an analysis generation object, the control device 112 may input a prompt to the generation AI that includes the first graph information I16 corresponding to that analysis generation object or the data used to generate the first graph information I16, and an analysis command requesting the generation of an analysis of the first graph information I16. The control device 112 may also display analysis result information based on the output of the generation AI to the user. The control device 112 of the server 110 may also determine which analysis command to input to the generation AI from a plurality of pre-prepared analysis command statements based on the classification condition information or graphing condition information used to generate the first graph information I16.

[0131] The control device 112 of the server 110 may determine the vertical and horizontal axes using a generating AI.

[0132] Furthermore, the classification condition information I13 may not be generated by user X's input processing, but may be automatically generated by the control device 112 of the server 110. That is, the control device 112 of the server 110 may pre-select one or more selective classification conditions from one or more classification conditions and generate selection condition information indicating one or more selected classification conditions. One or more selective classification conditions may be selected by the administrator of the server 110 in advance, or they may be selected by user X when user X starts using system 1.

[0133] In system 1b, the control device 112 of server 110 extracts real estate information I10 of properties similar to Building A, specifically properties located near Building A and properties with a total floor area close to that of Building A. However, the control device 112 of server 110 may also extract real estate information I10 of properties similar to Building A, for example, properties with a completion year close to that of Building A, or properties with a standard floor area close to that of Building A.

[0134] In addition, in systems 1,1a to 1f, the control device 112 of the server 110 may classify the target real estate information I110 into one or more categories based on the tenant information table shown in Figure 6. For example, the control device 112 of the server 110 can classify the target real estate information I110 into tenant industry categories.

[0135] In addition, in systems 1,1a to 1f, the control device 112 of server 110 may generate the first graph information I16 based on the tenant information table shown in Figure 7.

[0136] In addition, in systems 1,1a to 1f, the user terminal 10 may also perform processes executed by the server 110. In this case, the user terminal 10 obtains all real estate information I10 from the server 110.

[0137] In systems 1,1a to 1f, the server 110 may be implemented by a single computer or by multiple computers.

[0138] In addition, in systems 1,1a to 1f, the server 110 may generate graph image information for displaying the graph image and transmit the graph image information to the user terminal 10 as first graph information I16 and / or second graph information I26.

[0139] Note that the graphing conditions indicate the parameters used for the vertical axis 202 of the graph. However, the graphing conditions may also indicate the parameters used for both the vertical axis 202 and the horizontal axis 204 of the graph, or they may only indicate the parameters used for the horizontal axis 204. [Explanation of Symbols]

[0140] 1,1a~1f: System 10: User terminal 12: Control device 14:Storage device 16: Network Interface 18: Graphics Processing Unit 20: Display 26:Operation unit 28: Touch panel 42: Means for obtaining input information 44: Input information transmission control means 46: Classification condition information acquisition means 48: Classification condition information transmission control means 50: Means of acquiring graph information 52: Display control means 110: Server 112: Control device 114: Storage device 116: Network Interface 120: Method for extracting target real estate information 122: Classification condition information acquisition means 124: Category Classification Methods 126: Graph Information Generation Means 128: Means for obtaining graphing condition information 200: Graph 1 202: Vertical axis 204: Horizontal axis 210: Classification Selection Section 211: Checkbox 212: Axis selection section 300: Graph 2 302: Vertical axis 304: Horizontal axis A1: Graph display area A2: Property display area 114a: Property information DB 114b:Recruitment information DB 114c: Tenant Information Database 114d: Land Price Information Database I1: Property Information I2: Recruitment Information I3: Tenant Information I4: Land Price Information I5: Property Details I6: First Graph Information I10: Real Estate Information I11: Input Information I12: Extracted image information I13: Classification condition information I14: Graph Information I15: Graphing Conditions Information I16: First Graph Information I26: Second Graph Information I110: Target property information K1~K5,K11~K15,K21,K22,K31,K32,K41~K43: Series PG1, PG2: Program X: User

Claims

1. A system comprising one or more computers, The storage devices of the one or more computers mentioned above store multiple pieces of real estate information related to real estate, The control devices of the one or more computers described above are: Based on the input information generated by the user's input processing, one or more target property information is extracted from the multiple property information. To obtain classification condition information that indicates one or more selected classification conditions from one or more classification conditions for classifying the one or more target real estate information into one or more categories, Based on the classification criteria information, the one or more target real estate information is classified into one or more categories. Based on the one or more target property information, graph information is generated showing a graph having one or more series corresponding to each of the one or more categories. system.

2. The user can select one or more desired classification conditions from among one or more classification conditions. The control devices of the one or more computers described above are: In the process of obtaining the classification condition information, the classification condition information is obtained that indicates one or more selected classification conditions selected by the user. The system according to claim 1.

3. The control devices of the one or more computers described above are: Obtain graphing condition information indicating the graphing conditions for generating the aforementioned graph, In the process of generating the graph information, graph information is generated that shows a graph having one or more series corresponding to each of the one or more categories, based on the one or more target property information and the graphing condition information. The system according to claim 1.

4. The control devices of the one or more computers described above are: In the process of generating the graph information, one or more numerical values ​​used in the graph are calculated for each of the one or more categories based on one or more parameters included in the one or more target property information. The system according to claim 3.

5. The user can select the desired graphing conditions from several types of graphing conditions. The control devices of the one or more computers described above are: In the process of obtaining the graphing condition information, the graphing condition information corresponding to the graphing condition selected by the user is obtained. The system according to claim 3 or claim 4.

6. The graphing conditions mentioned above indicate the parameters used on the vertical axis and / or horizontal axis of the graph. The system according to claim 3 or claim 4.

7. Each of the aforementioned multiple pieces of real estate information includes a relationship between the first parameter and time, The graph has a first axis which is the time axis and a second axis which shows the magnitude of the first parameter. The control devices of the one or more computers described above are: In the process of generating the graph information, the average value of the first parameter included in the one or more target property information belonging to the one or more categories is calculated as one or more numerical values ​​used in the graph. The system according to claim 4.

8. The first parameter is the rent of the property, the area of ​​the property, or the number of listings for the property. The system according to claim 7.

9. Each of the aforementioned multiple pieces of real estate information includes a first parameter and a second parameter, The graph has a first axis representing the time axis and a second axis representing the magnitude of the third parameter. The control devices of the one or more computers described above are: In the process of generating the graph information, a third parameter obtained based on the first and second parameters included in the one or more target property information belonging to the one or more categories is calculated as one or more numerical values ​​used in the graph. The system according to any one of claims 1 to 3.

10. The third parameter is the occupancy rate of the property, the vacancy rate of the property, or the price per tsubo of the property. The system according to claim 9.

11. Each of the aforementioned multiple pieces of real estate information includes a first parameter and a second parameter, The graph has a first axis representing the magnitude of the first parameter and a second axis representing the magnitude of the second parameter. The control devices of the one or more computers described above are: In the process of generating the graph information, a first parameter included in the one or more target property information belonging to the one or more categories is calculated as one or more numerical values ​​used in the graph, and a second parameter included in the one or more target property information belonging to the one or more categories is calculated as one or more numerical values ​​used in the graph. The system according to any one of claims 1 to 3.

12. The aforementioned real estate information includes the address of the property, the distance from the property to the nearest station, the year the property was built, or the floor plan of the property. The system according to any one of claims 1 to 4.

13. The aforementioned input information indicates search conditions for extracting one or more target property information from the multiple property information. The system according to any one of claims 1 to 4.

14. The aforementioned input information indicates the property specified by the user, The control devices of the one or more computers described above are: In the process of extracting one or more target property information, property information related to the property specified by the user, and property information related to properties similar to the property specified by the user are extracted as one or more target property information. The system according to any one of claims 1 to 4.

15. Each of the aforementioned multiple pieces of real estate information includes a first parameter and a second parameter, The control devices of the one or more computers described above are: In the process of generating the graph information, first graph information is generated showing a first graph having one or more series corresponding to each of the one or more categories, based on the first parameter included in the one or more target real estate information, and second graph information is generated showing a second graph having one or more series corresponding to each of the one or more categories, based on the second parameter included in the one or more target real estate information. The system according to any one of claims 1 to 3.

16. The aforementioned one or more computers are equipped with a machine learning model, The control devices of the one or more computers described above are: In the process of generating the graph information, by inputting the one or more target real estate information into the machine learning model, one or more second values ​​used in the graph are calculated for each of the one or more categories. The aforementioned second numerical value of 1 or more is a value that interpolates or extrapolates the aforementioned numerical value of 1 or more in the graph. The system according to claim 4.

17. The computer's storage device stores multiple pieces of real estate information related to real estate, The control unit of the aforementioned computer, Based on the input information generated by the user's input processing, one or more target property information is extracted from the multiple property information. To obtain classification condition information that indicates one or more selected classification conditions from one or more classification conditions for classifying the one or more target real estate information into one or more categories, Based on the classification criteria information, the one or more target properties are classified into one or more categories. Based on the one or more target real estate information, graph information is generated showing a graph having one or more series corresponding to each of the one or more categories. program.

18. A terminal that is connected to a computer in a manner that enables communication, The storage device of the aforementioned computer stores multiple pieces of real estate information related to real estate, The control device of the aforementioned terminal is The input information is obtained through the user input process of the aforementioned terminal. By transmitting the aforementioned input information to the computer, the computer is made to extract one or more target property information from the plurality of property information. The user input process obtains classification condition information indicating one or more selected classification conditions from one or more classification conditions for classifying the one or more target real estate information into one or more categories. By transmitting the classification condition information to the computer, the computer generates graph information showing a graph having one or more series. The aforementioned graph information is obtained from the computer, Based on the graph information, the graph is displayed on the terminal's display. The one or more series mentioned above correspond to each of the one or more categories into which the one or more subject properties are classified based on the classification condition information. Terminal.

19. A program that runs on a terminal that is connected to a computer in a communicative manner, The storage device of the aforementioned computer stores multiple pieces of real estate information related to real estate, The program is controlled by the terminal's control device. The terminal's user input process allows the input information to be obtained. By transmitting the aforementioned input information to the computer, the computer is made to extract one or more target property information from the multiple property information, The user input process obtains classification condition information indicating one or more selected classification conditions from one or more classification conditions for classifying the one or more target real estate information into one or more categories. By transmitting the classification condition information to the computer, graph information showing a graph having one or more series is generated. The aforementioned graph information is obtained from the computer. Based on the graph information, the graph is displayed on the terminal's display. The one or more series mentioned above correspond to each of the one or more categories into which the one or more subject properties are classified based on the classification condition information. program.

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