Systems, terminals and programs

Abstract

An object of the present invention is to provide a system, a terminal and a program capable of obtaining trends in real estate information for each attribute of real estate. [Solution] The present invention is a system including one or more computers. A storage device of the one or more computers stores a plurality of real estate information related to real estate. A control device of the one or more computers extracts one or more target real estate information from the plurality of real estate information based on input information generated by a user's input process, acquires classification condition information indicating one or more selected classification conditions selected 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 condition information, and generates graph information indicating 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 technology]

[0002] As an invention related to a conventional system, for example, a revenue evaluation device described in Patent Document 1 is known. In this system, the distribution analysis function generates rent distribution data, vacancy distribution data, and turnover distribution data showing the turnover of rental contracts from rental real estate advertisement data for a wide area including the location of the evaluation target property and for a predetermined period going back to the past. The rent and vacancy calculation function extracts data corresponding to the property information and access information of the evaluation target property from the rent distribution data and vacancy distribution data, and calculates the rent and vacancy rate of the evaluation target property. The operating income calculation function calculates operating income according to the calculated rent and vacancy rate of the evaluation target property. The operating expense calculation function extracts data corresponding to property information from the turnover distribution data, and calculates the operating expenses of the evaluation target property. The revenue calculation function calculates the revenue of the evaluation target property from the operating income, operating expenses, and yield. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP2015-191648A Summary of the Invention [Problem to be solved by the invention]

[0004] Meanwhile, real estate has attributes such as area, layout, etc. Trends in real estate information such as rent for real estate have characteristics for each attribute. Therefore, users want to know the trends in real estate information for each attribute of real estate.

[0005] SUMMARY OF THE PRESENT EMBODIMENT An object of the present invention is to provide a system, a terminal, and a program that can obtain real estate information trends for each real estate attribute. [Means for solving the problem]

[0006] The first form is, A system comprising one or more computers, The one or more computer storage devices store a plurality of real estate information related to real estate; The one or more computer controllers include: Extracting one or more pieces of target real estate information from the plurality of pieces of real estate information based on input information generated by a user's input process; Obtaining 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; classifying the one or more target real estate information into one or more categories based on the classification condition information; generating 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; It is a system.

[0007] The second form is The user can select one or more desired selection classification conditions from one or more classification conditions, The one or more computer controllers include: In the process of acquiring the classification condition information, the classification condition information indicating one or more selected classification conditions selected by the user is acquired. The system according to the first aspect.

[0008] The third form is The one or more computer controllers include: acquiring graphing condition information indicating graphing conditions for generating the graph; In the process of generating the graph information, graph information showing a graph having one or more series corresponding to each of the one or more categories is generated based on the one or more target real estate information and the graphing condition information. The system according to the first aspect.

[0009] The fourth form is The one or more computer controllers include: In the process of generating I, one or more numerical values ​​to be 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 real estate information. The system according to the third aspect.

[0010] The fifth form is The user can select a desired graphing condition from a plurality of types of graphing conditions, The one or more computer controllers include: In the process of acquiring the graphing condition information, the graphing condition information corresponding to the graphing condition selected by the user is acquired. The system according to the third or fourth aspect.

[0011] The sixth form is The graphing conditions indicate parameters to be used on the vertical axis and / or the horizontal axis of the graph. The system according to any one of the third to fifth aspects.

[0012] The seventh form is Each of the plurality of pieces of real estate information includes a relationship between a first parameter and a time, the graph has a first axis which is a time axis and a second axis which indicates the magnitude of the first parameter, The one or more computer controllers include: In the process of generating the graph information, an average value of a 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 ​​to be used in the graph. The system according to the fourth aspect.

[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 real estate listings, The system according to the seventh aspect.

[0014] The ninth form is Each of the plurality of pieces of real estate information includes a first parameter and a second parameter; the graph has a first axis which is a time axis and a second axis which indicates the magnitude of a third parameter; The one or more computer controllers include: 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 ​​to be used in the graph. The system according to any one of the first to third aspects.

[0015] The tenth form is The third parameter is an occupancy rate of the real estate, a vacancy rate of the real estate, or a price per tsubo of the real estate, The system according to the ninth aspect.

[0016] The eleventh form is Each of the plurality of pieces of real estate information includes a first parameter and a second parameter; the graph has a first axis indicating a magnitude of the first parameter and a second axis indicating a magnitude of the second parameter, The one or more computer controllers include: In the process of generating the graph information, a 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 ​​to be used in the graph, and a 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 ​​to be used in the graph. The system according to any one of the first to third aspects.

[0017] The 12th form is The real estate information includes an address of the real estate, a distance from the real estate to a nearest station, an age of the real estate, or a floor plan of the real estate. The system according to any one of the first to eleventh aspects.

[0018] The 13th form is The input information indicates search conditions for extracting one or more pieces of target real estate information from the plurality of pieces of real estate information. The system according to any one of the first to twelfth aspects.

[0019] The 14th form is The input information indicates a real estate property designated by the user, The one or more computer controllers include: In the process of extracting the one or more pieces of target real estate information, real estate information related to the real estate specified by the user and real estate information related to real estate similar to the real estate specified by the user are extracted as the one or more pieces of target real estate information. The system according to any one of the first to thirteenth aspects.

[0020] The fifteenth form is Each of the plurality of pieces of real estate information includes a first parameter and a second parameter; The one or more computer controllers include: In the process of generating the graph information, first graph information showing a first graph having one or more series corresponding to each of the one or more categories is generated based on the first parameter included in the one or more target real estate information, and second graph information showing a second graph having one or more series corresponding to each of the one or more categories is generated based on the second parameter included in the one or more target real estate information. The system according to any one of the first to third aspects.

[0021] The 16th form is the one or more computers include a machine learning model; The one or more computer controllers include: In the process of generating the graph information, the one or more pieces of target real estate information are input to the machine learning model to calculate one or more second numerical values ​​to be used in the graph for each of the one or more categories; The one or more second numerical values ​​are values ​​that interpolate or extrapolate the one or more numerical values ​​in the graph. The system according to any one of the fourth to eleventh aspects.

[0022] The 17th form is The computer storage device stores a plurality of pieces of real estate information related to real estate; A control device of the computer, Extracting one or more pieces of target real estate information from the plurality of pieces of real estate information based on input information generated by a user's input process; acquiring classification condition information indicating one or more selected classification conditions selected from one or more classification conditions for classifying the one or more target real estate information into one or more categories; Classifying the one or more target real estate into one or more categories based on the classification condition information; generating 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 pieces of target real estate information; It is a program.

[0023] The 18th form is A terminal communicatively connected to a computer, The computer storage device stores a plurality of pieces of real estate information related to real estate; The control device of the terminal, Acquire input information through input processing by a user of the terminal; By transmitting the input information to the computer, the computer is caused to extract one or more pieces of target real estate information from the plurality of pieces of real estate information; Obtaining classification condition information indicating one or more selected classification conditions selected from one or more classification conditions for classifying the one or more target real estate information into one or more categories through an input process by the user; transmitting the classification condition information to the computer, thereby causing the computer to generate graph information indicating a graph having one or more series; obtaining the graph information from the computer; Displaying the graph on a display of the terminal based on the graph information; The one or more series correspond to one or more categories into which the one or more target real estate properties are classified based on the classification condition information. It is a terminal.

[0024] The 19th form is A program executed on a terminal communicably connected to a computer, The computer storage device stores a plurality of pieces of real estate information related to real estate; The program includes: Acquire input information through input processing by a user of the terminal; By transmitting the input information to the computer, the computer is caused to extract one or more pieces of target real estate information from the plurality of pieces of real estate information; acquiring, by the user's input process, classification condition information indicating one or more selected classification conditions selected from one or more classification conditions for classifying the one or more target real estate information into one or more categories; transmitting the classification condition information to the computer to generate graph information showing a graph having one or more series; obtaining said graph information from said computer; Displaying the graph on a display of the terminal based on the graph information; The one or more series correspond to one or more categories into which the one or more target real estate properties are classified based on the classification condition information. It is a program. Effect of the Invention

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

[0026] [Figure 1] FIG. 1 is an explanatory diagram of the system 1. [Diagram 2] FIG. 2 is a block diagram of the user terminal 10. [Diagram 3] FIG. 3 is a block diagram of the server 110. [Figure 4] FIG. 4 is a diagram showing a real estate information table. [Diagram 5] FIG. 5 is a diagram showing a recruitment information table. [Figure 6] FIG. 6 is a diagram showing a tenant information table. [Figure 7] FIG. 7 is a diagram showing a roadside land price information table. [Figure 8] FIG. 8 shows an image displayed on the display 20 of the user terminal 10. As shown in FIG. [Figure 9] FIG. 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] FIG. 10 shows an image displayed on the display 20 of the user terminal 10. As shown in FIG. [Figure 11] FIG. 11 shows an image displayed on the display 20 of the user terminal 10. As shown in FIG. [Figure 12] FIG. 12 shows an image displayed on the display 20 of the user terminal 10. As shown in FIG. [Figure 13] FIG. 13 shows an image displayed on the display 20 of the user terminal 10. As shown in FIG. [Figure 14] FIG. 14 shows an image displayed on the display 20 of the user terminal 10. As shown in FIG. [Figure 15] FIG. 15 shows an image displayed on the display 20 of the user terminal 10. As shown in FIG. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

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

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

[0029] The system 1 shown in Fig. 1 includes a user terminal 10 (one or more computer terminals) and a server 110 (one or more computers). The user terminal 10 and the server 110 are connected to each other so as to be able to communicate with each other via a communication network. The network may be the Internet, an intranet, or the like.

[0030] The user terminal 10 is a computer. The user terminal 10 is an information processing device used by a user X. The user terminal 10 is, for example, a smartphone, a tablet terminal, or a personal computer. As shown in FIG. 2, the 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 a Read Only Memory (ROM), a Random Access Memory (RAM), and a storage (for example, a flash memory or a hard disk).

[0032] The program PG2 includes, for example, the following programs: ·OS (Operating System) programs Applications that process information (e.g., web browsers or target apps described below)

[0033] The data includes, for example, the following data: Databases referenced in information processing Data obtained by performing information processing (i.e., the results of performing information processing)

[0034] The control device 12 executes a program PG2 stored in the storage device 14 to realize the functions of the user terminal 10. The control device 12 is, for example, a circuit including 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 an input information acquiring means 42, an input information transmission control means 44, a classification condition information acquiring means 46, a classification condition information transmission control means 48, a graph information acquiring means 50, and a display control means 52 as functional blocks.

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

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

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

[0039] The system 1 may include a plurality of user terminals 10.

[0040] The server 110 is a computer. The server 110 is a Web server that stores data of Web pages. As shown in FIG. 3, the server 110 includes a control device 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 a Read Only Memory (ROM), a Random Access Memory (RAM), and a storage (for example, a flash memory or a hard disk).

[0042] The control device 112 executes a program PG1 stored in the storage device 114 to realize the functions of the server 110. The control device 112 is, for example, a circuit including 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 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 as functional blocks.

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

[0045] [Database] The databases held by the storage device 114 of the server 110 will be described. Fig. 4 is a diagram showing a real estate information table. Fig. 5 is a diagram showing a recruitment information table. Fig. 6 is a diagram showing a tenant information table. Fig. 7 is a diagram showing a land price information table.

[0046] As shown in FIG. 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 a property information table shown in FIG. 4. The property information table includes a plurality of property information I1. The property information I1 describes detailed information on a building having rooms for which rental is being recruited. In this embodiment, the property information I1 includes a property ID, a property name, an address (the address of the real estate), an asset type, a year of completion, a rented area, a total floor area, a ceiling height, a floor load, a number of rooms, a nearest station, an age (an age of the real estate), a standard floor area, a walking distance from the station (a distance from the real estate to the nearest station), a price per tsubo, a rent, and a latitude and longitude. The property information table may be provided for each asset type.

[0047] The recruitment information DB 114b stores the recruitment information table shown in FIG. 5. The recruitment information table includes a plurality of recruitment information I2. The recruitment information I2 describes detailed information about a room that is being offered for rent. The recruitment information I2 includes a recruitment ID, a property ID, a rental portion, a floor plan (floor plan of the real estate), a rental portion area, an offering price, a first information acquisition date, and a recruitment status. The control device 112 of the server 110 generates new recruitment information I2 every time a room of the property is offered for rent, and records the recruitment information I2 in the recruitment information table of FIG. 5. The first information acquisition date is the date on which the recruitment information I2 is recorded in the recruitment information table. Therefore, there are as many pieces of recruitment information I2 as the number of times the same room is offered for rent. However, the recruitment IDs of the recruitment information I2 for the same room are different from each other.

[0048] The tenant information DB 114c stores the tenant information table shown in FIG. 6. The tenant information table includes a plurality of pieces of tenant information I3. The tenant information I3 describes detailed information on the tenants residing in the property. The tenant information I3 includes the tenant ID, the tenant name, the property ID, the tenant's business type, the number of employees, and the occupancy period. Note that the occupancy period for rooms currently accepting applications is left blank.

[0049] The road price information DB 114d stores the road price information table shown in Fig. 7. The road price information table includes a plurality of road price information I4. The road price information I4 describes information on the road price of each area. The road price information I4 includes the area, road number, latitude and longitude, road price, and the second information acquisition date.

[0050] In this specification, the plurality of property information I1, the plurality of recruitment information I2, the plurality of tenant information I3, and the plurality of land price information I4 are collectively referred to as the plurality of real estate information I10. Therefore, the storage device 114 of the server 110 (one or more computers) stores the plurality of real estate information I10 related to real estate. In addition, real estate is a collective term for a building (property) and a room.

[0051] [System 1 operation] Next, the operation of the system 1 will be described with reference to the drawings. Fig. 8 is a diagram showing an image displayed on the display 20 of the user terminal 10.

[0052] First, an overview of the operation of the system 1 will be described. The system 1 displays a graph image shown in FIG. 8 on the user terminal 10. The graph image shown in FIG. 8 includes a graph display area A1 and a property display area A2. The graph display area A1 includes a first graph 200. The first graph 200 includes a vertical axis 202 and a horizontal axis 204. In the first graph 200 of FIG. 8, the parameter used for the vertical axis 202 is the price per tsubo. 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-ku, Tokyo.

[0053] The first graph 200 has one or more series. The first graph 200 shown in FIG. 8 has five series K1 to K5. Series K1 shows the relationship between the price per tsubo for a room with a one-room layout and time. Series K2 shows the relationship between the price per tsubo for a room with a one-kitchen room layout and time. Series K3 shows the relationship between the price per tsubo for a room with a one-bedroom, one-dining room, and kitchen layout and time. Series K4 shows the relationship between the price per tsubo for a room with a two-bedroom, two-dining room, and kitchen layout and time. Series K5 shows the relationship between the price per tsubo for a room with a three-bedroom, two-dining room, and kitchen layout and time.

[0054] Furthermore, the property display area A2 includes a plurality of property detailed information I5. The property detailed information I5 describes information about the property referenced when generating the first graph information I16 showing the first graph 200. The first graph information I16 shows the first graph 200 having one or more series K1 to K5 corresponding to one or more categories, respectively. The first graph information I16 includes a check box 211. Information about the property for which the check box 211 is checked is reflected in the first graph 200.

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

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

[0057] When the control device 12 of the user terminal 10 reads out the program PG2 stored in the storage device 14, the program PG2 causes the control device 12 of the user terminal 10 to execute the operations described below. 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 the programs.

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

[0059] The control device 12 (input information acquisition means 42) of the user terminal 10 acquires input information I11 through 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), thereby causing the server 110 (one or more computers) to extract one or more pieces of target real estate information I110 from the multiple pieces of real estate information I10. In response, 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 the multiple real estate information I10 based on the input information I11 generated by the input process of the 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 whose address includes Chiyoda-ku, Tokyo from the property information table of FIG. 4. The control device 112 of the server 110 extracts one or more recruitment information I2 and one or more tenant information I3 containing the property ID contained in the extracted one or more property information I1 from the recruitment information table of FIG. 5 and the tenant information table of FIG. 6. As a result, 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 extraction result image information I12 for displaying the extraction result image shown in FIG. 10 based on 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 (step S103). The extraction result image includes a graph display area A1 and a property display area A2, similar to the graph image shown in FIG. 8. However, the graph display area A1 of the extraction result image does not include a graph. On the other hand, the property display area A2 includes multiple property detailed information I5. The multiple property detailed information I5 corresponds 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 extraction result image information I12 to the user terminal 10 via the network interface 16 (step S104). In response, the network interface 16 of the user terminal 10 receives the extraction result image information I12 and outputs the extraction result image information I12 to the control device 12. As a result, the control device 12 of the user terminal 10 acquires the extraction result image information I12 (step S3). Then, the control device 12 of the user terminal 10 causes the display 20 to display the extraction result image shown in FIG. 10 based on the extraction result image information I12 (step S4).

[0063] The user X can select one or more desired selected classification conditions from one or more classification conditions in the extraction result image shown in FIG. 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 FIG. 10 includes a classification selection unit 210. The classification selection unit 210 includes a plurality of buttons selected by the user X in order to classify 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 into one or more categories. The classification selection unit 210 includes an "overall" button, a "floor plan" button, a "year of construction" button, and a "walk to station" button. The user X can touch any of the "overall" button, the "floor plan" button, the "year of construction" button, or the "walk to station" button by operating the operation unit 26 of the user terminal 10. In this embodiment, the user X touches the "floor plan" button. In response, the control device 12 (classification condition information acquisition means 46) of the user terminal 10 acquires classification condition information I13 indicating one or more selected classification conditions selected from the selection conditions for classifying one or more pieces of target real estate information I110 into one or more categories through an input process by the user X (step S5). That is, the control device 12 of the user terminal 10 acquires classification condition information I13 indicating one or more selected classification conditions selected by the user X. In this embodiment, the classification condition information I13 indicates that one or more pieces of target real estate information I110 are classified into one or more categories based on the floor plan.

[0064] Next, the control device 12 (classification condition information transmission control means 48) of the user terminal 10 transmits the classification condition information I13 to the server 110 (one or more computers) via the network interface 16 (step S6), thereby causing the server 110 (one or more computers) to generate graph information I14 indicating a first graph 200 having one or more series. In response, 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 the classification condition information I13 indicating one or more selected classification conditions selected from one or more classification conditions for classifying one or more pieces of 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 pieces of target real estate information I110 (one or more pieces of property information I1, one or more pieces of recruitment information I2, and one or more pieces of 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 pieces of target real estate information I110 are classified into one or more categories based on the floor plan. Therefore, the control device 112 of the server 110 refers to the floor plan of one or more pieces of recruitment information I2 included in the one or more pieces of target real estate information I110. Then, the control device 112 of the server 110 classifies one or more pieces of target real estate information I110 into the category of "1 room", the category of "1K", the category of "1LDK", the category of "2LDK" and the category of "3LDK".

[0066] Meanwhile, the user X can select a desired graphing condition from a plurality of types of graphing conditions. The graphing condition is a condition for generating the first graph 200. Specifically, the graphing condition indicates a parameter to be used for the vertical axis of the first graph 200. Therefore, the extraction result image shown in FIG. 10 includes an axis selection section 212. The axis selection section 212 includes a plurality of buttons for the user X to select a parameter to be used for the vertical axis 202 of the first graph 200. The axis selection section 212 includes a button for "price per tsubo", a button for "total rent", a button for "occupancy rate", and a button for "number of units available". The 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 section 26 of the user terminal 10. In this embodiment, the user X touches the button for "price per tsubo". In response, 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 the 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.

[0067] Next, the control device 12 of the user terminal 10 transmits the graphing condition information I15 to the server 110 (one or more computers) via the network interface 16 (step S8). In response, 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 the 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 the graphing condition information I15 corresponding to the graphing conditions selected by the user X.

[0068] Next, the control device 112 (graph information generating means 126) of the server 110 generates the 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 the 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 offering price (first parameter) and a rented area (second parameter). Then, the control device 112 of the server 110 calculates the unit price per tsubo (third parameter) obtained based on the offering price (first parameter) and the rented area (second parameter) included in the one or more target real estate information I110 (one or more recruitment information I2) belonging to one or more categories as one or more numerical values ​​used in the first graph 200.

[0069] More specifically, the control device 112 of the server 110 arranges one or more pieces of recruitment information I2 in chronological order based on the first information acquisition date of the one or more pieces of recruitment information I2. Then, the control device 112 of the server 110 calculates the average value of the unit price per tsubo of one or more pieces of recruitment information I2 belonging to the same category and the same year and month. For example, the control device 112 of the server 110 divides the value three times the asking price included in each of the one or more pieces of recruitment information I2 belonging to the category of "1 room" and January 2024 by the area of ​​the rented portion. As a result, the control device 112 of the server 110 calculates the unit price per tsubo of each of the one or more pieces of recruitment information I2 belonging to the category of "1 room" and January 2024. The control device 112 of the server 110 calculates the total value of the unit price per tsubo of the one or more pieces of recruitment information I2 belonging to the category of "1 room" and January 2024. The control device 112 of the server 110 divides the total price per tsubo by the number of one or more pieces of recruitment information I2 belonging to the category "1 room" and January 2024. As a result, the control device 112 of the server 110 calculates the average price per tsubo of one or more pieces of recruitment information I2 belonging to the category "1 room" and January 2024. The control device 112 of the server 110 then repeats the same process to calculate the average price per tsubo of one or more pieces of recruitment information I2 for all categories and all years and months. As a result, the control device 112 of the server 110 generates the first graph information I16. The first graph information I16 includes a large number of coordinate data in which the average price per tsubo is associated with the category and the year and month.

[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). In response, 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 causes the display 20 to display a graph image shown in FIG. 8 based on the first graph information I16 (step S10). More specifically, the graph image includes a first graph 200. The first graph 200 has a horizontal axis 204 (first axis) which is a time axis and a vertical axis 202 (second axis) which indicates the magnitude of the price per tsubo (third parameter). The control device 12 of the user terminal 10 plots a large number of coordinate data included in the first graph information I16 on 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. As a result, series K1 to K5 are generated. After this, this process ends.

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

[0073] The control device 12 of the user terminal 10 may display a graph image shown in Fig. 11 on the display 20. The graph image shown in Fig. 11 includes a first graph 200. The first graph 200 includes a vertical axis 202 and a horizontal axis 204. In the first graph 200 of Fig. 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-ku, Tokyo. The occupancy rate is the number of rented rooms divided by the total number of rooms multiplied by 100.

[0074] The first graph 200 has one or more series. The first graph 200 shown in FIG. 11 has five series K11 to K15. The series K11 shows the relationship between the occupancy rate of properties built 6 to 10 years ago and time. The series K12 shows the relationship between the occupancy rate of properties built 0 to 5 years ago and time. The series K13 shows the relationship between the occupancy rate of properties built 11 to 15 years ago and time. The series K14 shows the relationship between the occupancy rate of properties built 16 to 20 years ago and time. The series K15 shows the relationship between the occupancy rate of properties built 21 years ago or older and time. The process of the control device 112 of the server 110 generating graph image information for displaying the graph image shown in FIG. 11 will be described below with reference to the flowchart shown in FIG. 9. Note that steps S1 to S4, S9, S10, S101 to S104, and S109 in the process of generating graph image information for displaying the graph image shown in FIG. 11 are the same as steps S1 to S4, S9, S10, S101 to S104, and S109 in the process of generating graph image information for displaying the graph image shown in FIG. 8, and therefore will not be described.

[0075] The user X can select a desired selection classification condition from one or more classification conditions in the extraction result image shown in FIG. 10. The classification condition 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 FIG. 10 includes a classification selection unit 210. The classification selection unit 210 includes a plurality of buttons selected by the user X in order to classify 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 into one or more categories. The classification selection unit 210 includes an "overall" button, a "floor plan" button, a "year of construction" button, and a "walk to station" button. The user X can touch any of the "overall" button, the "floor plan" button, the "year of construction" button, or the "walk to station" button by operating the operation unit 26 of the user terminal 10. Therefore, the user X touches the "year of construction" button. In response, the control device 12 of the user terminal 10 acquires classification condition information I13 indicating one or more selected classification conditions selected from one or more classification conditions for classifying one or more pieces of target real estate information I110 into one or more categories through an input process by the user X (step S5). In this embodiment, the classification condition information I13 indicates that one or more pieces of target real estate information I110 are classified into one or more categories based on the building age.

[0076] Next, the control device 12 of the user terminal 10 transmits the classification condition information I13 to the server 110 (one or more computers) via the network interface 16 (step S6), thereby causing the server 110 (one or more computers) to generate graph information I14 indicating a first graph 200 having one or more series. In response, 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 acquires the classification condition information I13 indicating one or more selected classification conditions selected from one or more classification conditions for classifying one or more pieces of 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 is classified into one or more categories according to the building age. Therefore, the control device 112 of the server 110 refers to the building age 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 one or more property information I1 into a 0-5 year category, a 6-10 year category, an 11-15 year category, a 16-20 year category, and a 21 year or more category. Furthermore, the control device 112 of the server 110 classifies the recruitment information I2 and tenant information I3 including the property ID of the one or more property information I1 classified into the 0-5 year category into the 0-5 year category. The control device 112 of the server 110 classifies the recruitment information I2 and tenant information I3 including the property ID of one or more property information I1 classified in the 6 to 10 years category into the 6 to 10 years category. The control device 112 of the server 110 classifies the recruitment information I2 and tenant information I3 including the property ID of one or more property information I1 classified in the 11 to 15 years category into the 11 to 15 years category. The control device 112 of the server 110 classifies the recruitment information I2 and tenant information I3 including the property ID of one or more property information I1 classified in the 16 to 20 years category into the 16 to 20 years category. The control device 112 of the server 110 classifies the recruitment information I2 and tenant information I3 including the property ID of one or more property information I1 classified in the 21 years or more category into the 21 years or more category.

[0078] Meanwhile, the user X can select a desired graphing condition from a plurality of types of graphing conditions. The graphing condition is a condition for generating the first graph 200. Specifically, the graphing condition indicates a parameter to be used for the vertical axis of the first graph 200. Therefore, the extraction result image shown in FIG. 10 includes an axis selection section 212. The axis selection section 212 includes a plurality of buttons for the user X to select a parameter to be used for the vertical axis 202 of the first graph 200. The axis selection section 212 includes a button for "price per tsubo", a button for "total rent", a button for "occupancy rate", and a button for "number of units available". The 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 section 26 of the user terminal 10. In this embodiment, the user X touches the button for "occupancy rate". In response, the control device 12 of the user terminal 10 acquires graphing condition information I15 indicating graphing conditions for generating the first graph 200 (step S7). In the embodiment, the graphing condition information I15 indicates that the parameter used for the vertical axis 202 of the first graph 200 is the operating rate.

[0079] Next, the control device 12 of the user terminal 10 transmits the graphing condition information I15 to the server 110 (one or more computers) via the network interface 16 (step S8). In response, 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 acquires the 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 the graphing condition information I15 corresponding to the graphing conditions selected by the 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 recruitment 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). Also, the number of recruitment information I2 (multiple real estate information) that is recruiting is the number of vacant rooms (second parameter). Then, the control device 112 of the server 110 calculates an 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 recruitment information I2) belonging to one or more categories, as one or more numerical values ​​used in the first graph 200.

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

[0082] In the first graph 200, one or more pieces of target real estate information I110 are classified into one or more categories based on the building age. However, in the first graph 200, one or more pieces of target real estate information I110 may be classified into one or more categories based on the walking distance from the station, the town area, or the city, ward, town, or village.

[0083] Also, the control device 12 of the user terminal 10 may display a graph image shown in FIG. 12 on the display 20. The graph image shown in FIG. 12 includes a first graph 200. The first graph 200 includes a vertical axis 202 and a horizontal axis 204. In the first graph 200 of FIG. 12, the parameter used for the vertical axis 202 is the number of units available for sale. The parameter used for the horizontal axis 204 is time. The first graph 200 may show the relationship between the number of units available for sale in Chiyoda-ku, Tokyo and time. Note that, in the first graph 200, one or more pieces of target real estate information I110 are not classified into one or more categories. However, in the first graph 200, one or more pieces of target real estate information I110 may be classified into one or more categories according to the age of the building, the layout, and the price per tsubo.

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

[0085] [effect] According to the system 1, the tendency of the real estate information I10 can be obtained for each attribute of the room (real estate). More specifically, the control device 112 of the server 110 acquires classification condition information I13 indicating one or more selected classification conditions selected from one or more classification conditions for classifying one or more pieces of target real estate information I110 into one or more categories. As a result, the control device 112 of the server 110 can classify one or more pieces of target real estate information I110 into one or more categories based on the classification condition information I13. Through this classification process, one or more pieces of target real estate information I110 are classified into one or more categories according to the attributes of the one or more pieces of target real estate information I110. Furthermore, the control device 112 of the server 110 can generate first graph information I16 indicating a first graph 200 having series K1 to K5 corresponding to each of one or more categories based on one or more pieces of target real estate information I110. The series K1 to K5 express the tendency of one or more pieces of target real estate information I110 for each attribute of the room (real estate). As a result, the system 1 can obtain trends in the real estate information I10 for each attribute of the room (real estate).

[0086] In the system 1, the user X can select one or more desired selected classification conditions from one or more classification conditions. Then, the control device 112 of the server 110 acquires classification condition information I13 indicating the one or more selected classification conditions selected by the user X. This allows the user X to view the first graph 200 generated according to the one or more selected classification conditions that he or she desires.

[0087] In the system 1, the user X can select a desired graphing condition from a plurality of types of graphing conditions. Then, the control device 112 of the server 110 acquires the graphing condition information I15 corresponding to the graphing condition selected by the user X. As a result, the control device 112 of the server 110 can generate the first graph information I16 indicating the first graph 200 having the series K1 to K5 corresponding to each of the plurality of categories based on one or more pieces of target real estate information I110 and the graphing condition information I15. As a result, the user X can view the first graph 200 generated under the desired graphing condition. In this embodiment, the graphing condition indicates a parameter used for the vertical axis 202 of the first graph 200. Therefore, the user X can view the first graph 200 having the desired vertical axis 202.

[0088] In the system 1, the first graph 200 using parameters not included in the real estate information I10 can be obtained. More specifically, each of the multiple real estate information I10 includes the asking price (first parameter) and the rented area (second parameter). Then, the control device 112 of the server 110 calculates the price per tsubo (third parameter) obtained based on the asking price (first parameter) and the rented area (second parameter) 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. In this way, the control device 112 of the server 110 calculates the price per tsubo (third parameter) not included in the target real estate information I110 based on the asking price (first parameter) and the rented area (second parameter). As a result, in the system 1, the first graph 200 using parameters not included in the real estate information I10 can be obtained.

[0089] (First Modification) Next, a system 1a according to a first modified example will be described with reference to the drawings. Fig. 14 is a diagram showing an image displayed on the display 20 of the user terminal 10. As shown in Figs.

[0090] The system 1a differs from the system 1 in that the graph image shown in Fig. 14 includes a first graph 200 and a second graph 300. The following describes this difference with reference to the drawings.

[0091] First graph 200 includes vertical axis 202 and horizontal axis 204. In first graph 200 of Figure 14, the parameter used for vertical axis 202 is vacancy rate. The parameter used for horizontal axis 204 is time. First graph 200 shows the relationship between vacancy rate and time in Chiyoda-ku, Tokyo, and the relationship between vacancy rate and time in Shibuya-ku, Tokyo.

[0092] The first graph 200 has one or more series. The first graph 200 shown in Fig. 14 has two series K21 and K22. The series K21 shows the relationship between the vacancy rate and time in Chiyoda-ku, Tokyo. The series K22 shows the relationship between the vacancy rate and time in Shibuya-ku, 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 available (first parameter) included in one or more pieces of target real estate information I110. The number of units available is the number of pieces of information I2 currently available for sale included in one or more pieces of target real estate information I110.

[0094] The second graph 300 includes a vertical axis 302 and a horizontal axis 304. In the second graph 300 of FIG. 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. The parameter used for the horizontal axis 304 is time. The second graph 300 shows the relationship between the available area stock and time in Chiyoda-ku, Tokyo, and the relationship between the available area stock and time in Shibuya-ku, Tokyo.

[0095] The second graph 300 has one or more series. The second graph 300 shown in Fig. 14 has two series K31 and K32. The series K31 shows the relationship between the stock of available floor space in Chiyoda-ku, Tokyo and time. The series K32 shows the relationship between the stock of available floor space in Shibuya-ku, Tokyo and time.

[0096] In step S108, the control device 112 of the 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 rented portion area (second parameter) included in one or more pieces of target real estate information I110. The control device 112 of the server 110 calculates the area stock for sale by calculating the sum of the rented portion areas. The other configurations of the system 1a are the same as those of the system 1, so a description thereof will be omitted. The system 1a can achieve the same effects as the system 1.

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

[0098] (Second Modification) Next, a system 1b according to a second modified example will be described with reference to the drawing. Fig. 15 is a diagram showing an image displayed on the display 20 of the user terminal 10.

[0099] The system 1b differs from the system 1 in that the first graph 200 includes information for each property. The following describes this difference with reference to the drawings.

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

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

[0102] The control device 12 of the user terminal 10 acquires input information I11 through input processing of a 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), thereby causing the server 110 (one or more computers) to extract one or more pieces of target real estate information I110 from the multiple pieces of real estate information I10. In response, 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 the real estate information I10 related to the A building (real estate) specified by the user X, and the real estate information I10 related to a property (real estate) similar to the A building (real estate) specified by the user X, as one or more pieces of target real estate information I110 (step S102). More specifically, the A building is specified in the input information I11. Then, the control device 112 of the server 110 extracts the property information I1 of the A building, the property information I1 of a property (real estate) similar to the A building, and one or more pieces of property information I1 whose address includes Chiyoda-ku, Tokyo, from the property information table of FIG. 4. The property information I1 of the property (real estate) similar to the A building is the property information I1 whose total floor area is close to the total floor area of ​​the A building. The one or more pieces of property information I1 whose address includes Chiyoda-ku, Tokyo, are one or more pieces of property information I1 related to a property located near the A building. The control device 112 of the server 110 extracts one or more pieces of recruitment information I2 that contain the property ID contained in the one or more pieces of extracted property information I1 from the recruitment information table of Fig. 5. As a result, the control device 112 of the server 110 extracts one or more pieces of property information I1 and one or more pieces of recruitment information I2 that are one or more pieces of target real estate information I110.

[0104] Next, the control device 112 of the server 110 generates extraction result image information I12 for displaying the extraction result image shown in FIG. 10 based on one or more property information I1 and one or more recruitment information I2, which are one or more target real estate information I110 (step S103). The extraction result image includes a graph display area A1 and a property display area A2, similar to the graph image shown in FIG. 8. However, the graph display area A1 of the extraction result image does not include a graph. On the other hand, the property display area A2 includes multiple property detailed information I5. The multiple property detailed information I5 correspond to one or more target real estate information (one or more property information I1 and one or more recruitment 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 extraction result image information I12 to the user terminal 10 via the network interface 16 (step S104). In response, the network interface 16 of the user terminal 10 receives the extraction result image information I12 and outputs the extraction result image information I12 to the control device 12. As a result, the control device 12 of the user terminal 10 acquires the extraction result image information I12. Then, the control device 12 of the user terminal 10 causes the display 20 to display the extraction result image shown in FIG. 10 based on the extraction result image information I12 (step S3).

[0106] The user X can select one or more desired selected classification conditions from one or more classification conditions in the extraction result image shown in FIG. 10. The classification conditions are conditions for classifying one or more target real estate information I110 into one or more categories. Therefore, the user X selects A Building as the category of the series K41, selects a competing property as the category of the series K42, and selects Chiyoda-ku, Tokyo as the category of the series K43 in the extraction result image shown in FIG. 10. In response, the control device 12 of the user terminal 10 acquires classification condition information I13 indicating one or more selected classification conditions selected from the classification conditions for classifying one or more target real estate information I110 into one or more categories by the input process of the user X (step S5). That is, the control device 12 of the user terminal 10 acquires classification condition information I13 indicating one or more selected classification conditions selected by the user X.

[0107] Next, the control device 12 of the user terminal 10 transmits the classification condition information I13 to the server 110 (one or more computers) via the network interface 16 (step S6), thereby causing the server 110 (one or more computers) to generate graph information I14 indicating a first graph 200 having one or more series. In response, 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 acquires the classification condition information I13 indicating one or more selected classification conditions selected from one or more classification conditions for classifying one or more pieces of 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 recruitment 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 recruitment 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 recruitment information I2, and one or more tenant information I3) including the property name of A building into the category of "A building". The control device 112 of the server 110 refers to the address and total floor area of ​​one or more recruitment 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 and one or more recruitment information I2) that includes an address close to the address of the A building and a total floor area close to the total floor area of ​​the A building into the category of "competitive property". The control device 112 of the server 110 refers to the address of one or more recruitment 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 recruitment information I2, and one or more tenant information I3) that includes Chiyoda-ku, Tokyo in its address into the category of "Chiyoda-ku, Tokyo". After this, the processing performed by the system 1b is the same as that of the system 1, so the description will be omitted. The system 1b can achieve the same effect as the system 1.

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

[0110] (Third Modification) Next, a system 1c according to a third modified example will be described.

[0111] The system 1c differs from the system 1 in that the parameter used for the horizontal axis of the first graph 200 is not time. The following describes this difference with reference to the drawings.

[0112] A first graph 200 in system 1c includes a vertical axis 202 and a horizontal axis 204. In first graph 200, the parameter used for vertical axis 202 is price per tsubo. The parameter used for horizontal axis 204 is rental area. Also, in first graph 200, circles are plotted. The size of the circle indicates the number of units available. First graph 200 shows the relationship between price per tsubo, rental area, and number of units available. The other configurations of system 1c are the same as those of system 1, so explanations are omitted. System 1c can achieve the same effects as system 1.

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

[0114] In the systems 1, 1a to 1c, the graphing condition information I15 is not essential. Therefore, the control device 112 of the server 110 may generate the first graph information I16 showing the first graph 200 having one or more series corresponding to one or more categories, based on one or more pieces of 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 determined in advance, rather than being selected by the user X.

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

[0116] In the systems 1, 1a to 1c, the control device 112 of the server 110 uses the third parameter calculated from the first parameter and the second parameter included in the property information I1 on the vertical axis (second axis). However, the vertical axis (second axis) may indicate the magnitude of the first parameter included in the property information I1. In this case, each of the multiple real estate information I10 (multiple offering information I2) includes the relationship between the first parameter (e.g., offering price) and time. The first graph 200 has a horizontal axis (first axis) that is the time axis and a vertical axis (second axis) that indicates the magnitude of the first parameter (offering price). Then, the control device 112 of the 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., offering price) 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 an average value of a first parameter (asking price) included in one or more pieces of target real estate information I110 belonging to one or more categories as one or more numerical values ​​used in the first graph 200. Note that the first parameter may be the asking price of a room (rent of the real estate), the rentable area of ​​a room (area of ​​the real estate), the number of rooms (real estate) offered, the occupancy rate of the real estate, the vacancy rate of the real estate, or the price per tsubo of the real estate.

[0117] In the 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 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., rental area). In this case, each of the multiple real estate information I10 (multiple property information I1 and multiple asking information I2) includes the first parameter (e.g., asking price) and the second parameter (e.g., rental 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 ​​to be used in the first graph 200, and calculates a second parameter (e.g., rental area) included in the one or more target real estate information I110 belonging to one or more categories as one or more numerical values ​​to be used in the graph.

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

[0119] In the system 1, the control device 112 of the server 110 calculates the price per tsubo (third parameter, the price per tsubo of the real estate) obtained based on the asking price (first parameter) and the rented area (second parameter) included in one or more target real estate information I110 (one or more offering information I2) belonging to one or more categories as one or more numerical values ​​to be used in the first graph 200. However, the control device 112 of the server 110 may also calculate the room occupancy rate (the occupancy rate of the real estate) or the room vacancy rate (the vacancy rate of the real estate) as one or more numerical values ​​to be used in the first graph 200.

[0120] The control device 112 of the server 110 performs the processes of steps S106 to S108 every 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 processes of steps S106 to S108 previously performed in the storage device 114. Then, the control device 112 of the server 110 may read out the results from the storage device 114 when a request is retransmitted from the user terminal 10.

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

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

[0123] In addition, in the system 1, when the user X touches the series K1 by operating the operation unit 26 of the user terminal 10, the control device 12 of the user terminal 10 may display on the display 20 a property display area A2 including detailed information I5 of multiple properties belonging to the series K1.

[0124] In the system 1, when the user X touches a button included in the category selection section 210 by operating the operation section 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 the user X presses the button included in the category selection section 210, the series of the first graph 200 changes.

[0125] In the system 1, when the 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. In other words, when the user X presses the button included in the classification selection unit 210, the vertical axis of the first graph 200 changes.

[0126] In the system 1, the graph image shown in Fig. 8 may include a map of Chiyoda-ku, Tokyo. In this case, an icon is placed at each of the locations of a plurality of rooms for which applications are being accepted. The icons belonging to the series K1, the series K2, the series K3, the series K4, and the series K5 may have different colors, shapes, etc., so that they can be distinguished from one another.

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

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

[0129] The control device 112 of the server 110 may analyze the contents of the first graph information I16 using a generation AI based on the first graph information I16. In this case, the control device 112 of the server 110 may generate, as the analysis result information, an analysis result predicting the time when the price per tsubo will peak, an analysis result analyzing the trend of the asking price between regions, etc. Also, the control device 112 of the server 110 may generate, as the analysis result information, advice on whether the room being offered is a good deal or not, using the generation AI. For example, the control device 112 of the server 110 inputs the first graph information I16 or the data used in generating the first graph information I16 to the generation AI (e.g., a Transformer model such as GPT, etc.) and a prompt including a command corresponding to the analysis target selected by the user (e.g., predicting the time when the price per tsubo will peak, the trend of the asking price between regions, creating a summary of the graph, etc.), and outputs the analysis result based on the result output from the generation AI as the analysis result information. This allows the user to read the analysis result of the graph even if he or she does not have expertise in real estate.

[0130] In addition, the control device 112 of the server 110 may input the first graph information I16 or a prompt including the first graph information I16 and an analysis command to the generation AI, and output an analysis result based on the result output from the generation AI as analysis result information. The generation AI is a Transformer model such as GPT. The generation AI may be provided by the server 110 or an external server. The analysis command may be, for example, "predict the time when the price per tsubo will peak from the input data," "describe the trend of the asking price between regions from the input data," "create a summary of the input graph," etc. This allows the user to read the analysis result of the graph and obtain an explanation of the graph even if he or she does not have expertise in real estate. At this time, the analysis command may be input by the user, or may be selected and determined by the user from predetermined command statements. 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, and when the user selects the analysis / generation object, input a prompt including the first graph information I16 corresponding to the analysis / generation object or data used to generate the first graph information I16 and an analysis command statement requesting generation of the analysis of the first graph information I16 to the generation AI, and display analysis result information based on the output result of the generation AI to the user. The control device 112 of the server 110 may determine an analysis command statement to be input to the generation AI from among a plurality of analysis command statements prepared in advance, 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] The classification condition information I13 may be automatically generated by the control device 112 of the server 110, instead of being generated by an input process by the user X. That is, the control device 112 of the server 110 may select one or more selected classification conditions from one or more classification conditions in advance, and generate selection condition information indicating the one or more selected classification conditions. The one or more selected classification conditions may be selected by an administrator of the server 110 by setting them in advance, or may be selected by the user X when the user X starts using the system 1.

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

[0134] In the 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 Fig. 6. The control device 112 of the server 110 may classify the target real estate information I110 into categories of tenant business types, for example.

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

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

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

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

[0139] The graphing conditions indicate the parameters used for the vertical axis 202 of the graph. However, the graphing conditions may indicate the parameters used for the vertical axis 202 and the horizontal axis 204 of the graph, or may 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 section 28: Touch panel 42: Input information acquisition means 44: Input information transmission control means 46: Classification condition information acquisition means 48: Classification condition information transmission control means 50: Means of obtaining graph information 52: Display control means 110: Server 112: Control device 114: Storage device 116: Network interface 120: Means for extracting target real estate information 122: Classification condition information acquisition means 124: Category classification means 126: Graph information generating means 128: Graphing condition information acquisition means 200: First graph 202: Vertical axis 204: Horizontal axis 210: Classification selection section 211: Checkbox 212: Axis selection section 300: 2nd graph 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 DB 114d:Roadside price information DB I1: Property Information I2: Recruitment Information I3: Tenant information I4: Road price information I5: Property details I6: First graph information I10: Real Estate Information I11: Input information I12: Extraction result image information I13: Classification condition information I14:Graph information I15:Graphing condition information I16: First graph information I26: 2nd graph information I110: Target real estate 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 one or more computer storage devices store a plurality of property information related to the property; The one or more computer controllers include: Extracting a plurality of pieces of target real estate information from the plurality of pieces of real estate information based on input information generated by a user's input process; Obtain classification condition information indicating one or more selected classification conditions selected from one or more classification conditions for classifying the plurality of target real estate information into a plurality of categories; classifying the plurality of target real estate information into a plurality of categories based on the classification condition information; generating graph information showing a graph having a plurality of series corresponding to each of the plurality of categories based on the plurality of target real estate information; system.

2. The user can select one or more desired selection classification conditions from one or more classification conditions, The one or more computer controllers include: In the process of acquiring the classification condition information, the classification condition information indicating one or more selected classification conditions selected by the user is acquired. The system of claim 1 .

3. The one or more computer controllers include: acquiring graphing condition information indicating graphing conditions for generating the graph; In the process of generating the graph information, graph information showing a graph having a plurality of series corresponding to each of the plurality of categories is generated based on the plurality of target real estate information and the graphing condition information. The system of claim 1 .

4. The one or more computer controllers include: In the process of generating the graph information, one or more numerical values ​​to be used in the graph are calculated for each of the plurality of categories based on one or more parameters included in the plurality of target real estate information. The system of claim 3.

5. The user can select a desired graphing condition from a plurality of types of graphing conditions, The one or more computer controllers include: In the process of acquiring the graphing condition information, the graphing condition information corresponding to the graphing condition selected by the user is acquired. A system according to claim 3 or claim 4.

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

7. Each of the plurality of pieces of real estate information includes a relationship between a first parameter and a time, the graph has a first axis which is a time axis and a second axis which indicates the magnitude of the first parameter, The one or more computer controllers include: In the process of generating the graph information, an average value of a first parameter included in the plurality of target real estate information belonging to the plurality of categories is calculated as one or more numerical values ​​to be used in the graph. The system of claim 4.

8. The first parameter is the rent of the real estate, the area of ​​the real estate, or the number of real estate listings. The system of claim 7.

9. Each of the plurality of pieces of real estate information includes a first parameter and a second parameter; the graph has a first axis which is a time axis and a second axis which indicates the magnitude of a third parameter; The one or more computer controllers include: In the process of generating the graph information, a third parameter obtained based on the first parameter and the second parameter included in the plurality of target real estate information belonging to the plurality of categories is calculated as one or more numerical values ​​to be used in the graph. A system according to any one of claims 1 to 3.

10. The third parameter is an occupancy rate of the real estate, a vacancy rate of the real estate, or a price per square meter of the real estate, The system of claim 9.

11. Each of the plurality of pieces of real estate information includes a first parameter and a second parameter; the graph has a first axis indicating a magnitude of the first parameter and a second axis indicating a magnitude of the second parameter; The one or more computer controllers include: In the process of generating the graph information, a first parameter included in the plurality of target real estate information belonging to the plurality of categories is calculated as one or more numerical values ​​to be used in the graph, and a second parameter included in the plurality of target real estate information belonging to the plurality of categories is calculated as one or more numerical values ​​to be used in the graph. A system according to any one of claims 1 to 3.

12. The real estate information includes an address of the real estate, a distance from the real estate to a nearest station, an age of the real estate, or a floor plan of the real estate. A system according to any one of claims 1 to 4.

13. The input information indicates search conditions for extracting a plurality of target real estate information from the plurality of real estate information. A system according to any one of claims 1 to 4.

14. The input information indicates a real estate property designated by the user, The one or more computer controllers include: In the process of extracting the plurality of target real estate information, real estate information related to the real estate specified by the user and real estate information related to real estate similar to the real estate specified by the user are extracted as the plurality of target real estate information. A system according to any one of claims 1 to 4.

15. Each of the plurality of pieces of real estate information includes a first parameter and a second parameter; The one or more computer controllers include: In the process of generating the graph information, first graph information showing a first graph having a plurality of series corresponding to each of the plurality of categories is generated based on the first parameter included in the plurality of target real estate information, and second graph information showing a second graph having a plurality of series corresponding to each of the plurality of categories is generated based on the second parameter included in the plurality of target real estate information. A system according to any one of claims 1 to 3.

16. the one or more computers include a machine learning model; The one or more computer controllers include: In the process of generating the graph information, the plurality of target real estate information are input to the machine learning model to calculate one or more second numerical values ​​to be used in the graph for each of the plurality of categories; The one or more second numerical values ​​are values ​​that interpolate or extrapolate the one or more numerical values ​​in the graph. The system of claim 4.

17. The computer storage device stores a plurality of pieces of real estate information related to real estate; A control device of the computer, Extracting a plurality of pieces of target real estate information from the plurality of pieces of real estate information based on input information generated by a user's input process; acquiring classification condition information indicating one or more selected classification conditions selected from one or more classification conditions for classifying the plurality of target real estate information into a plurality of categories; Classifying the plurality of target real estate information into a plurality of categories based on the classification condition information; generating graph information showing a graph having a plurality of series corresponding to each of the plurality of categories based on the plurality of target real estate information; program.

18. A terminal communicatively connected to a computer, The computer storage device stores a plurality of pieces of real estate information related to real estate; The control device of the terminal, Acquire input information through input processing by a user of the terminal; By transmitting the input information to the computer, the computer extracts a plurality of pieces of target real estate information from the plurality of pieces of real estate information; acquiring, by the user's input process, classification condition information indicating one or more selected classification conditions selected from one or more classification conditions for classifying the plurality of target real estate information into a plurality of categories; transmitting the classification condition information to the computer, thereby causing the computer to generate graph information showing a graph having a plurality of series; obtaining the graph information from the computer; Displaying the graph on a display of the terminal based on the graph information; The plurality of series correspond to a plurality of categories into which the plurality of target real estate information are classified based on the classification condition information. Terminal.

19. A program executed on a terminal communicably connected to a computer, The computer storage device stores a plurality of pieces of real estate information related to real estate; The program includes: Acquire input information through input processing by a user of the terminal; The input information is transmitted to the computer, whereby the computer extracts a plurality of pieces of target real estate information from the plurality of pieces of real estate information; acquiring, by the user's input process, classification condition information indicating one or more selected classification conditions selected from one or more classification conditions for classifying the plurality of target real estate information into a plurality of categories; transmitting the classification condition information to the computer to generate graph information showing a graph having a plurality of series; obtaining said graph information from said computer; Displaying the graph on a display of the terminal based on the graph information; The plurality of series correspond to a plurality of categories into which the plurality of target real estate information are classified based on the classification condition information. program.

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