JP2022083450A - Information processing device, information processing method, and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an information processing device, information processing method and program enabling effective appeal for purchase of an estate for relocation to a person living in a rental.

SOLUTION: An information processing device according to the present invention includes: a step S8 of extracting one or more articles from an article database storing information of a plurality of articles for sale or a rental database storing information of a plurality of rental based on input rental information which is information of rental input by a first user; and step S10 of outputting information representing one or more extracted articles respectively to the first user.

SELECTED DRAWING: Figure 4

COPYRIGHT: (C)2022,JPO&INPIT

Description

There is an application for application of Article 30, Paragraph 2 of the Patent Act September 11, 2nd year of Reiwa https: // www. edit-tech. co. jp / news / 246 / https: //market. dr-asset. jp / https: // recorder. dr-asset. jp / September 14, 2nd year of Reiwa https: // PR TIMES. jp / main / html / rd / p / 000000006.000050271. html

The present invention relates to an information processing device, an information processing method, and a program, and relates to an information processing device, an information processing method, and a program used for selling real estate properties such as condominiums.

In recent years, in the sale of real estate properties such as condominiums, the use of sales sites installed on the Web is increasing. According to the sales site, it is easier to reach potential consumers than waiting at a real estate agent's store, so it is possible to expect an improvement in the closing rate.

Patent Document 1 discloses an example of a sales support device used at a real estate sales site. The sales support device according to this example has a function of having a purchase applicant input a monthly desired payment amount and extracting and displaying real estate whose total monthly payment amount is less than or equal to the desired payment amount.

Patent No. 6386683

By the way, potential consumers of real estate include those who live in rental properties. That is, some people who live in rental properties are living with the idea that it may be better to buy than to continue renting, and such people are the potential demand for real estate. It can be said that he is a person. Therefore, there is a need for technology that can effectively appeal to people living in rental properties to purchase real estate for relocation. In this regard, it seems that the real estate suitable for the purchase applicant can be presented by using the technique described in Patent Document 1, but the purchase applicant arbitrarily inputs the desired monthly payment amount, which is the standard for extraction, in the first place. Therefore, the real estate presented was not always suitable for those who wished to purchase it.

Therefore, one of the objects of the present invention is to provide an information processing device, an information processing method, and a program that can effectively appeal to a person resident in a rental property to purchase real estate for relocation. be.

In addition, as a sales site provider, attracting good buyers who have high purchasing motivation and corresponding resources to their own site is one of the points to improve the contract rate, but all of them. Traditional sales sites that treat buyers equally have been difficult to attract good buyers.

Therefore, another object of the present invention is to provide an information processing device, an information processing method, and a program that can provide a sales site that can attract good buyers.

The information processing device according to the first aspect of the present invention extracts one or more properties from a database that stores information on a plurality of properties based on the input rental property information that is the rental property information input by the first user. It is an information processing device that outputs information indicating each of the extracted one or more properties to the first user.

The information processing device according to the second aspect of the present invention is a property database that stores information on sales properties input by the second user according to the selection of the second user who is the seller, and information on a plurality of sales properties. , And register in one of the private property databases that store information on multiple privately-sold properties, and register the information indicating the desired conditions of the purchased property entered by the third user who is the buyer in the condition database. Then, when the property for sale registered in the property database or the private property database matches the desired condition registered in the condition database, the information on the property for sale is distributed to the third user. , An information processing device.

The information processing method according to the first aspect of the present invention extracts one or more properties from a database that stores information on a plurality of properties based on the input rental property information that is the rental property information input by the first user. This is an information processing method including a step of outputting information indicating each of the extracted one or more properties to the first user.

The information processing method according to the second aspect of the present invention is a property database that stores information on sales properties input by the second user according to the selection of the second user who is the seller, and information on a plurality of sales properties. , And the step of registering in one of the private property databases that store the information of multiple privately-sold properties, and the information indicating the desired conditions of the purchased property entered by the third user who is the buyer. When the step of registering in, the property for sale registered in the property database or the private property database, and the desired condition registered in the condition database match, the property for sale is sold to the third user. It is an information processing method including a step of distributing information.

The program according to the first aspect of the present invention is a step of extracting one or more properties from a database that stores information of a plurality of properties based on the input rental property information which is the rental property information input by the first user. It is a program for causing a computer to execute a step of outputting information indicating each of the extracted one or more properties to the first user.

The program according to the first aspect of the present invention is a property database that stores information on properties for sale input by the second user according to the selection of the second user who is the seller, and information on a plurality of properties for sale, and a property database. , Register in the condition database the step of registering in one of the private property databases that store information of multiple privately-sold properties, and the information indicating the desired conditions of the purchased property entered by the third user who is the buyer. When the step to be performed, the property for sale registered in the property database or the private property database, and the desired condition registered in the condition database match, the information of the property for sale is provided to the third user. It is a program to make a computer execute the steps to be delivered.

According to the first aspect of the present invention, since the property for sale is extracted based on the information of the rental property input by the user, the person resident in the rental property can purchase the real estate for relocation. It becomes possible to appeal effectively.

According to the second aspect of the present invention, it is permitted to register the information of the privately-sold property in the private property database provided separately from the property database and to register the desired conditions in the condition database in advance. Since information on properties for sale that meet the desired conditions is distributed to the buyer, it is possible to provide a sales site that can attract good buyers.

It is a figure which shows the system structure of the information processing system 1 by embodiment of this invention. It is a figure which shows the basic hardware composition of each of the information processing apparatus 10 and the user terminal 30, 31. It is a figure which shows the structure of the condominium database 20, the rental property database 21, and the property database 22. It is a flow chart which shows the process flow of the sale property extraction process executed by a planner server 11. It is a flow chart which shows the detail of the appropriate rent estimation processing executed in step S4 of FIG. It is a flow chart which shows the detail of the appropriate purchase price estimation process executed in step S5 of FIG. It is a figure which shows the example of the screen which is displayed on the display of the user terminal 30 which is a smartphone. It is a sequence diagram of the sale property extraction process executed by the planner server 11. It is a figure which shows the structure of a private property database 23, a member database 24, a condition database 25, and a delivery database 26. It is a flow chart which shows the process flow of the sale property registration process executed by the member's market server 12. It is a flow diagram which shows the process flow of the desired condition registration process executed by a recommender server 13. It is a flow diagram which shows the process flow of the delivery process executed by a recommender server 13. (A) is a diagram showing a public type selection page 50 which is an example of a public type selection page displayed in step S40 of FIG. 10, and (b) is an information input page displayed in step S46 of FIG. It is a figure which shows the information input page 51 which is an example. It is a figure which shows the information input page 52 which is an example of the information input page displayed in step S52 of FIG. It is a figure which shows the distribution page 53 which is an example of the distribution page generated in step S66 of FIG. It is a sequence diagram of a part (up to registration in the distribution database 26) of the sale property registration process and the distribution process executed by the member's market server 12 and the recommender server 13. It is a sequence diagram of the rest of the member registration process, the desired condition registration process, and the delivery process executed by the recommender server 13.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings.

FIG. 1 is a diagram showing a system configuration of the information processing system 1 according to the embodiment of the present invention. As shown in the figure, the information processing system 1 has a configuration in which the information processing apparatus 10 and the user terminals 30 and 31 are connected to each other via the network 3. The network 3 is, for example, the Internet, and is connected to various WEB sites including an information processing device 10 and user terminals 30 and 31, as well as a sales site 2 that sells real estate properties such as condominiums.

The information processing device 10 is a server computer, and functionally, it has three types of servers, a planner server 11, a members market server 12, and a recommender server 13, as well as an apartment database 20, a rental property database 21, a property database 22, and non-recommended servers. It has seven types of databases: a public property database 23, a member database 24, a condition database 25, and a distribution database 26.

Of these, the planner server 11 is a server that causes a user residing in the rental property to input information on the rental property in residence, extracts the property for sale based on the input information, and presents it to the user. , The apartment database 20, the rental property database 21, and the property database 22. The member's market server 12 is a server that functions as a sales site for selling properties such as condominiums on the network 3, and is connected to the recommender server 13 and the property database 22. The recommender server 13 is a server for selling the property uploaded to the member's market server 12 privately, and the member's market server 12, the property database 22, the private property database 23, the member database 24, the condition database 25, And is connected to the distribution database 26. The details of each will be described separately later. In the present embodiment, each server and each database will be described as being mounted in one information processing device 10, but each server and each database will be distributed and mounted in a plurality of information processing devices 10. It may be that.

The user terminals 30 and 31 are computers that the user personally uses, respectively. FIG. 1 shows an example in which the user terminal 30 is a smartphone and the user terminal 31 is a notebook-type personal computer, but the specific models of the user terminals 30 and 31 are not limited thereto. For example, the user terminals 30 and 31 may be configured by a tablet computer or a desktop personal computer. Hereinafter, the description will be continued on the assumption that the user terminal 30 is a smartphone and the user terminal 31 is a personal computer.

FIG. 2 is a diagram showing a basic hardware configuration of each of the information processing apparatus 10 and the user terminals 30 and 31. As shown in the figure, in the information processing device 10 and the user terminals 30 and 31, the processor 101, the storage device 102, the communication device 103, the input device 104, and the output device 105 are mutually connected via the bus 106, respectively. It is configured to have a configuration connected to.

The processor 101 is a central processing unit that reads out and executes a program stored in the storage device 102. Each process described later as a process performed by the information processing device 10 and the user terminals 30 and 31 is realized by each processor 101 reading and executing a program stored in each storage device 102. The processor 101 is configured to be able to communicate with each part in the server via the bus 106, and controls each part and processes data stored in the storage device 102 according to the description of the program to be executed.

The storage device 102 is a device that temporarily or permanently stores various programs and various data. The storage device 102 usually has a plurality of storage devices such as a main storage device composed of a DRAM (Dynamic Random Access Memory) or an SRAM (Static Random Access Memory), an auxiliary storage device composed of a hard disk, an SSD (Solid State Drive), or the like. It consists of a combination of storage devices.

The communication device 103 is a device that executes communication with an external communication device (including the network 3 shown in FIG. 1) under the control of the processor 101. The communication method performed by the communication device 103 is not particularly limited, and examples thereof include a wired or wireless WAN (Wide Area Network) or a LAN (Local Area Network).

The input device 104 is a device that receives input from a user, and includes various input means such as a mouse, a keyboard, and a touch panel. The content of the user input received by the input device 104 is transmitted to the processor 101 via the bus 106. The output device 105 is a device that outputs to the user according to the control of the processor 101, and includes various output means such as a display and a speaker.

Hereinafter, the processing executed by the information processing apparatus 10 will be described in detail. In the following description, first, the processes executed by the planner server 11 will be described with reference to FIGS. 3 to 8, and then the processes executed by the members market server 12 and the recommender server 13 will be described with reference to FIGS. 9 to 9. It will be described with reference to FIG.

First, the process executed by the planner server 11 will be described. FIG. 3 is a diagram showing the structures of the condominium database 20, the rental property database 21, and the property database 22 connected to the planner server 11. Of these, the condominium database 20 is a database that stores information on condominiums as buildings, and is associated with the condominium ID for identifying the condominium, and has the property name (name of the condominium), address, latitude / longitude, and nearest. Station, walking from the nearest station (time required when walking from the nearest station), building structure (S, RC, SRC, etc.), date of construction (date when the condominium was built), total number of units, It is configured to store the yield (a numerical value that represents the superficial profitability of how much rent income can be obtained with respect to the property price).

The rental property database 21 is a database that stores information on properties such as a room in a condominium that is a unit for rent (hereinafter referred to as “rental property”), and is associated with a rental property ID for identifying a rental property. Condominium ID, rent, exclusive area, layout (3LDK, 1R, etc.), number of rooms (number of rooms included in the property), floor, balcony direction (south, east-southeast, etc.), corner room flag (whether it is a corner room) It is configured to store information such as whether or not it is remodeled), whether or not it has been reformed (information indicating whether or not it has been reformed), and the type of right (information indicating whether it is a condominium with a fixed-term leasehold or a condominium with ownership).

The property database 22 is a database that stores information on properties such as a room in a condominium, which is a unit of sale (hereinafter referred to as “judgment property”), and is associated with a sales property ID for identifying a sales property, and is a condominium. ID, price, price deviation value (profitability), occupied area, floor plan (3LDK, 1R, etc.), number of rooms (number of rooms included in the property), location floor, balcony direction (south, east-southeast, etc.), contract It is configured to store the presence / absence (information indicating whether or not the contract has been completed).

The data stored in the condominium database 20, the rental property database 21, and the property database 22 are registered in each database by the planner server 11 or the members market server 12. More specifically, the planner server 11 is configured to collect information on rental properties and sales properties by visiting one or more sales sites 2 on the network 3 and register them in each database. The member's market server 12 is configured to collect information on rental properties and properties for sale by receiving input from the seller or the manager of the rental property and register it in each database.

FIG. 4 is a flow chart showing a processing flow of the sale property extraction process executed by the planner server 11. The information processing device 10 plays a role of effectively appealing to the person residing in the rental property the purchase of real estate for relocation by executing the sale property extraction process by the planner server 11. Hereinafter, the content of the property extraction process for sale will be described in detail with reference to FIG.

The planner server 11 first generates an input page for information on the currently resident rental property (hereinafter referred to as "residential rental property") (hereinafter referred to as "input rental property information") and displays it on the displays of the user terminals 30 and 31. (Step S1).

FIG. 7 is a diagram showing an example of a screen displayed on the display of the user terminal 30 which is a smartphone. Although the display example on the smartphone is shown in the figure, the content is the same for the screen displayed on the user terminal 31 which is a personal computer. The information input page 40 shown in FIG. 7 is an example of the information input page displayed in step S1. As shown in the figure, the information input page 40 is wide, including an image image and a description, a property name input field 40a for inputting the property name of the condominium currently resident, and a rent input field 40b for inputting the rent. A size input field 40c for inputting a space, a location floor input field 40d for inputting a floor, a corner room button 40e for selecting whether or not it is a corner room, and a south facing button 40f for selecting whether or not it is facing south. It is configured to have a reformed button 40g for selecting whether or not it has been reformed, and a transition button 40h for advancing the process. Of these, the property name input field 40a is preferably configured by a combo box in which the property name of each condominium stored in the condominium database 20 can be selected by the user.

Returning to FIG. 4, the planner server 11 displaying the information input page 40 determines whether or not the transition button 40h in the information input page 40 is pressed (step S2). The planner server 11 that determines that the transition button 40h has been pressed in step S2 has basic information (nearest station, nearest station walk, construction) of the resident rental property indicated by the input rental property information input on the information input page 40. After acquiring (year, month, etc.) from the condominium database 20 (step S3), the appropriate rent estimation process (step S4) for estimating the appropriate rent of the resident rental property, and the appropriate purchase price of the resident rental property. The appropriate purchase price estimation process (step S5) for estimating the above is sequentially executed.

FIG. 5 is a flow chart showing details of the appropriate rent estimation process executed in step S4. As shown in the figure, the planner server 11 that has started the appropriate rent estimation process first extracts condominiums located in the vicinity of the resident rental property from the condominium database 20 (step S20). Specifically, the condominiums in the same ward as the resident rental property may be extracted based on the address in the condominium database 20, or the resident rental property may be extracted based on the nearest station in the condominium database 20. Condominiums with the same nearest station may be extracted, or condominiums whose distance from the rented property during residence is less than or equal to a predetermined value may be extracted based on the latitude and longitude in the condominium database 20.

Next, the planner server 11 extracts a property similar to the resident rental property (hereinafter referred to as “neighborhood similar rental property”) from the rental property (stored in the rental property database 21) of the condominium extracted in step S20. (Step S21). Specifically, the planner server 11 first acquires the occupied area of the rented property during residence, the walk from the nearest station, and the date of construction. The occupied area is a numerical value entered in the area input field 40c (see FIG. 7) of the information input page 40, and the nearest station walk and the date of construction are the information included in the basic information acquired in step S3. Is. The planner server 11 also acquires the condominium ID, the nearest station walk, and the date of construction of each condominium extracted in step S20 from the condominium database 20, and extracts the rental property having the acquired condominium ID from the rental property database 21. .. Then, the occupied area of the extracted rental property is acquired from the rental property database 21. The planner server 11 extracts neighborhood-like rental properties based on the occupied area of the residential rental property and other rental properties acquired as described above, the walk from the nearest station, and the date of construction. Specifically, properties whose occupied area, walking distance from the nearest station, and difference in construction date from the rented property during residence are within the predetermined values may be extracted as neighborhood-like rental properties. Here, an example of using the occupied area, walking from the nearest station, and the date of construction as criteria for similar judgment has been described, but it goes without saying that other criteria may be used.

Subsequently, the planner server 11 corrects the rent of the extracted neighborhood-like rental property so that the conditions other than the conditions used as the criteria for the similarity determination in step S21 meet the conditions of the resident rental property (step S22). .. This correction is made based on the information input on the information input page 40 and the information of the corresponding neighboring similar rental property. To give a specific example, if the floor where the rented property in residence is located is the lower floor and the floor where the rental property similar to the neighborhood is located is the higher floor, the rent of the rental property similar to the neighborhood is corrected downward. In addition, if the rented property in the neighborhood is a corner room and the rental property similar to the neighborhood is not a corner room, the rent of the rental property similar to the neighborhood is corrected in the upward direction. Furthermore, if the rented property in residence is facing south and the rental property similar to the neighborhood is facing north, the rent of the rental property similar to the neighborhood is corrected in the upward direction. In addition, if the rented property in residence has been renovated and the rental property similar to the neighborhood has not been renovated, the rent of the rental property similar to the neighborhood will be corrected in the upward direction. The degree of ascent and descent may be determined in advance by preparing a table including various cases and according to the stored contents of the table, or by having artificial intelligence learn various cases in advance and this artificial intelligence. It may be decided based on the output result of.

Finally, the planner server 11 obtains the average value of the corrected rent and acquires it as the appropriate rent of the rented property during residence (step S23), thereby ending the appropriate rent estimation process.

FIG. 6 is a flow chart showing details of the appropriate purchase price estimation process executed in step S5. As shown in the figure, the planner server 11 that has started the appropriate purchase price estimation process first extracts condominiums located in the vicinity of the resident rental property from the condominium database 20 (step S30). Specifically, as in step S20 described above, condominiums in the same ward as the resident rental property may be extracted based on the address in the condominium database 20, or the nearest station in the condominium database 20 may be extracted. Based on this, it may be possible to extract condominiums whose nearest station is the same as the resident rental property, or condominiums whose distance from the resident rental property is less than or equal to a predetermined value based on the latitude and longitude in the condominium database 20. It may be extracted. However, in step S30, it is preferable to extract the condominium in a geographically wide range as compared with the extraction in step S20 described above and step S34 described later. By doing so, in the subsequent step S31, it becomes possible to extract a large number of properties for calculating the yield.

Next, the planner server 11 extracts the condominium properties (sales properties and rental properties) extracted in step S30 from at least one of the property database 22 and the rental property database 21, and resembles the residential rental property from the extracted properties. Properties to be built (hereinafter referred to as “neighborhood similar properties”) are extracted (step S31). The similar determination criteria here may be the same as in step S21 described above.

Subsequently, the planner server 11 acquires the price and rent of each neighboring similar property extracted in step S31 (step S32). Specifically, the price and rent of the property for sale and the price and rent of the rental property are acquired or estimated from the price stored in the property database 22 and the rent stored in the rental property database 21.

Next, the planner server 11 calculates the yield of each neighborhood-like property by the following formula (1) using the price and rent of each neighborhood-like property acquired in step S32, and obtains the average value (step S33). ). However, A in the formula (1) is the price of each neighborhood-like property, B is the rent of each neighborhood-like property, and C is the yield of each neighborhood-like property.
C = (B × 12) / A × 100 ・ ・ ・ (1)

Next, the planner server 11 extracts condominiums located in the vicinity of the resident rental property from the condominium database 20 (step S34), and from the extracted condominium rental properties, a property similar to the resident rental property (neighborhood similar rental property). ) Is extracted (step S35). The details of the processing of steps S34 and S35 are the same as the processing of steps S20 and S21.

Next, the planner server 11 uses the following formula based on the average value of the yield calculated in step S33 and the rent of each neighboring similar rental property (set in the rental property database 21) extracted in step S35. The price of each neighborhood-like rental property is estimated by (2) (step S36). However, D in the formula (2) is the rent of each neighborhood-like rental property, E is the average value of the yield calculated in step S33, and F is the estimated value of the price of each neighborhood-like rental property.
F = (D × 12) × 100 / E ・ ・ ・ (2)

Finally, the planner server 11 obtains the average value of the prices estimated in step S36 and acquires it as the appropriate purchase price of the resident rental property (step S37), thereby ending the appropriate purchase price estimation process.

Return to FIG. The planner server 11 that has completed steps S4 and S5 calculates the loan repayment amount when the resident rental property is purchased based on the appropriate purchase price estimated in step S5 (step S6). In this calculation, it is preferable that the planner server 11 calculates the loan repayment amount using a predetermined repayment period and repayment method (fixed amount type, fixed rate type, etc.) and the latest interest rate. The information input page 40 shown in FIG. 7 may allow the user to input a repayment period and a repayment method, and calculate the loan repayment amount using the input repayment period and the repayment method. After that, the planner server 11 generates an information output page including the appropriate rent estimated in step S4 and the loan repayment amount calculated in step S6, and displays it on the displays of the user terminals 30 and 31 (step S7).

The information output page 41 shown in FIG. 7 is an example of the information output page displayed in step S7. The "current rent" included in the information output page 41 shown in the figure is the rent of the resident rental property input in the rent input field 40b of the information input page 40, and the "appropriate rent" is estimated in step S4. The rent is appropriate, and the “loan repayment amount” is the loan repayment amount calculated in step S6. The information output page 41 also displays the difference between the "current rent" and the "appropriate rent" and the difference between the "current rent" and the "loan repayment amount". By looking at this information output page 41, the user can see whether the current rent is appropriate and how much the loan repayment amount will be compared to the current rent if it is assumed that the rented property in residence is purchased. You can know.

Return to FIG. Subsequently, the planner server 11 extracts from the property database 22 a more preferable sale property that can be purchased at a price equivalent to the appropriate purchase price estimated in step S5 (step S8). The term "equivalent" here means that the difference between the price stored in the property database 22 and the appropriate purchase price estimated in step S5 is within a predetermined value. In addition, "more preferable" means, for example, that the occupied area is larger than that of a rented property during residence, the building date is new, or a popular area (for example, in the case of Tokyo, Chuo-ku, Chiyoda-ku, Minato-ku). , Bunkyo Ward, Shinjuku Ward, Shibuya Ward, etc.).

The planner server 11 determines whether or not the transition button of the information output page 41 (for example, the "next" button included in the information output page 41 of FIG. 7) is pressed (step S9). The planner server 11 that determines that the transition button has been pressed in step S9 generates an information output page including a list of properties for sale extracted in step S8, and displays it on the displays of the user terminals 30 and 31 (step S10).

The information output page 42 shown in FIG. 7 is an example of the information output page displayed in step S10. As shown in the figure, on the information output page 42, information on a plurality of properties for sale is listed together with a "view property" button and a "consult" button. The information input page 43 shown in FIG. 7 is an example of a page displayed when the user presses the "consult" button. The information input page 43 is a page for inputting user information and requests, and when the user presses the "inquire" button included in the information input page 43, the planner server 11 receives the input user information and requests. Generate an e-mail containing information on the corresponding resident rental property and property for sale and send it to a predetermined sales representative's e-mail address. As a result, the sales person can directly introduce the property for sale to the user who has accessed the information input page 40.

FIG. 8 is a sequence diagram of the sale property extraction process executed by the planner server 11. Hereinafter, by referring to FIG. 8, the processing performed by the planner server 11 will be described from another viewpoint.

The planner server 11 first visits one or more sales sites 2 and collects information on rental properties and sales properties from each (step S100). Then, based on the collected information, records of the condominium database 20, the rental property database 21, and the property database 22 are generated and registered in each (step S101).

Next, the planner server 11 accepts input of information on the rental property in which the user resides from the user terminals 30 and 31 (step S102), and acquires the basic information from the condominium database 20 (step S103). Subsequently, the planner server 11 extracts from the condominium database 20 and the rental property database 21 the neighborhood-like rental properties that are located in the vicinity of the resident rental property and are similar to the resident rental property (step S104). Then, after correcting the rent of the extracted neighborhood-like rental property so as to meet the conditions of the resident rental property (step S105), the average value of the corrected rent is presented to the user as the appropriate rent of the resident rental property. (Step S106).

Further, the planner server 11 extracts neighborhood-like properties similar to the rented property during residence from the condominium database 20 and the property database 22 (step S107), and the price thereof is obtained from the data stored in the property database 22 and the rental property database 21. And acquire the rent (step S108). Then, using the above-mentioned formula (1), the average value of the yields of the extracted similar properties in the neighborhood is calculated (step S109).

The planner server 11 further extracts neighborhood-like rental properties that are located in the vicinity of the resident rental property and that are similar to the resident rental property from the condominium database 20 and the rental property database 21 (step S110). Then, the price of each neighborhood-like rental property is estimated by substituting the average value of the yield calculated in step S109 and the rent of each neighborhood-like rental property extracted in step S110 into the above-mentioned equation (2), and the price thereof is estimated. From the result, the appropriate purchase price of the resident rental property is estimated (step S111). The planner server 11 calculates the loan repayment amount when the user purchases a residential rental property based on the appropriate purchase price thus estimated, and presents it to the user (step S112).

Finally, the planner server 11 extracts from the property database 22 a more preferable sale property that can be purchased at a price equivalent to the appropriate purchase price estimated in step S111 (step S113), and uses the extracted sales property information. (Step S114).

As described above, according to the planner server 11 according to the present embodiment, the property for sale is extracted based on the information of the rental property currently resident entered by the user, and therefore the person resident in the rental property. On the other hand, it will be possible to effectively appeal the purchase of real estate for relocation.

Further, according to the planner server 11 according to the present embodiment, since the appropriate rent and the appropriate purchase price of the rental property currently resident are presented, the user can use the case where the current rent is expensive or the case where the purchase is made. If your loan repayment amount is lower than your current rent, you can know those facts. Since this can be a motive for encouraging relocation, according to the planner server 11 according to the present embodiment, it is possible to more effectively appeal to the person resident in the rental property to purchase real estate for relocation. It will be possible.

The planner server 11 according to the present embodiment displayed the information output page including the list of properties for sale in step S10, but the information output page including the list of rental properties or the list of both the properties for sale and the rental properties. It may be possible to display an information output page including. In this case, the planner server 11 may rent a rental property at a price equivalent to the rent entered by the user on the information input page displayed in step S1 and extract a more preferable rental property from the rental property database 21. The term "equivalent" here means that the difference between the rent stored in the rental property database 21 and the rent entered by the user is within a predetermined value. In addition, "more preferable" means, for example, that the occupied area is larger than that of a rented property during residence, the building date is new, or a popular area (for example, in the case of Tokyo, Chuo-ku, Chiyoda-ku, Minato-ku). , Bunkyo Ward, Shinjuku Ward, Shibuya Ward, etc.).

Next, the processing executed by the members market server 12 and the recommender server 13 will be described. FIG. 9 is a diagram showing the structure of the private property database 23, the member database 24, the condition database 25, and the distribution database 26 connected to at least one of the members market server 12 and the recommender server 13. Of these, the structure of the private property database 23 is the same as that of the property database 22 shown in FIG. However, the private property database 23 stores only the information of the property for sale that the user who is the seller has selected to keep it private. This point will be explained in detail later.

The member database 24 is a database that stores member information of the service provided by the recommender server 13, and is configured to store name, address information, and the like in association with the member ID. The address information is, for example, an e-mail address or an SNS address. In the member database 24, information on a user who can be a buyer of a property for sale registered in the private property database 23 is registered in advance.

The condition database 25 is a database that stores information indicating desired conditions of the purchased property, and is associated with a member ID, a station, a station walk (time required when walking from the station), a price range, and an exclusive area. , Floor plan, number of rooms, balcony direction, etc. are memorized. As is understood from the fact that the member ID is included, the information registered in the condition database 25 is information indicating the desired conditions of the user registered in the member database 24.

The distribution database 26 is a database that stores information on sales properties that meet the desired conditions, and is configured to store the date on which distribution was executed in association with the combination of the condition ID and the sales property ID.

FIG. 10 is a flow chart showing a processing flow of the sale property registration process executed by the members market server 12. Further, FIG. 11 is a flow chart showing a processing flow of the desired condition registration process executed by the recommender server 13, and FIG. 12 is a flow chart showing a processing flow of the delivery process executed by the recommender server 13. be. The information processing apparatus 10 plays a role of providing a sales site that can attract good buyers by executing these processes by the members market server 12 and the recommender server 13. Hereinafter, the contents of each process will be described in detail with reference to FIGS. 10, 11, and 12.

First, referring to FIG. 10, the member's market server 12 that has started the sale property registration process first generates a public type selection page and displays it on the displays of the user terminals 30 and 31 (step S40).

FIG. 13A is a diagram showing a public type selection page 50 which is an example of the public type selection page displayed in step S40. The same figure and FIGS. 13 (b), 14 and 15 described later show examples of display on a personal computer, but the content is the same for the screen displayed on the user terminal 30 which is a smartphone. Is. As shown in FIG. 13 (a), the public type selection page 50 includes a selection button 50a for selecting a public sale and a selection button 50b for selecting a private sale.

Return to FIG. The member's market server 12 determines whether or not the user has selected the public sale by acquiring the type of the button pressed by the user on the displayed public type selection page 50 (step S41). Then, if it is determined that the sale by public is selected, the process proceeds to step S42, and if it is determined that the sale by public is not selected (the sale by private is selected), the process proceeds to step S46. ..

The member's market server 12, which has proceeded to the process in step S42, generates an information input page for the publicly-sold property and displays it on the displays of the user terminals 30 and 31 (step S42). Although not shown, the information input page displayed at this time may be the same as the information input page 51 shown in FIG. 13 (b) described later. The member's market server 12 determines whether or not the user has pressed the transition button on the information input page displayed in step S42 (step S43). Wait for confirmation (step S42). For example, this standby may be terminated when a page including a confirmation button is displayed on the terminal of the sales person and the sales person presses the confirmation button. By providing step S42, it becomes possible for the sales person to evaluate the property for sale (including correction of the input information) before registering the property for sale entered by the user in the property database 22. .. When the waiting is completed by pressing the confirmation button by the sales person, the member's market server 12 registers the sales property input by the user in the property database 22, and ends the sales property registration process for the public sale property.

On the other hand, the member's market server 12, which has proceeded to the process in step S46, generates an information input page for the privately-sold property and displays it on the displays of the user terminals 30 and 31 (step S46).

FIG. 13B is a diagram showing an information input page 51 which is an example of the information input page displayed in step S46. As shown in the figure, the information input page 51 has a name, telephone number, e-mail address, desired contact method, postal code and address of the location of the property for sale, apartment name, room number, exclusive area, desired time to sell, and desired sale. It is configured to have a field for inputting or selecting a price range and other items, and a transition button 51a.

Return to FIG. The member's market server 12 determines whether or not the user has pressed the transition button 51a on the information input page 51 displayed in step S46 (step S47), and if it is determined that the user has pressed the transition button 51a, the sales representative is in charge of sales. Wait for confirmation by the person (step S48). The content and meaning of this wait are the same as in step S44. When the standby is completed by pressing the confirmation button by the sales person, the member's market server 12 sends the property for sale entered by the user to the recommender server 13 and registers it in the private property database 23 via the recommender server 13. .. By the processing up to this point, the member's market server 12 ends the sale property registration process for the privately-sold property.

Next, referring to FIG. 11, the recommender server 13 that has started the desired condition registration process first confirms whether or not the connected user is a member registered in the member database 24. Authenticate the member (step S50). Then, it is determined whether or not the user is a member based on the result of member authentication (step S51), and if it is a member, the process proceeds to step S52, while if it is not a member, the desired condition registration process is terminated. This prevents users who are not members from registering desired conditions.

The recommender server 13, which has proceeded with the process in step S52, generates an information input page of desired conditions and displays it on the displays of the user terminals 30 and 31 (step S52).

FIG. 14 is a diagram showing an information input page 52 which is an example of the information input page displayed in step S52. As shown in the figure, the information input page 52 includes a field for inputting or selecting an area of a desired property, a property image, and the like, and a transition button 52a. The field for inputting or selecting an area is configured so that the user can select the input method from several input methods such as an area of interest, a line / station, and a ward. The field for inputting or selecting a property image is configured so that the user can select from a plurality of predetermined images. In addition, it goes without saying that a field for inputting or selecting other information such as the price range of the desired property, the occupied area, the floor plan, the number of rooms, the balcony direction, etc. may be provided in the information input page 52.

Return to FIG. The recommender server 13 determines whether or not the user has pressed the transition button 52a on the information input page 52 displayed in step S52 (step S53). Then, when it is determined that the button has been pressed, the input information is registered in the condition database 25 (step S54), and the desired condition registration process is terminated.

Finally, with reference to FIG. 12, the distribution process performed by the recommender server 13 will be described. The recommender server 13 is configured to execute this distribution process in response to the registration of the privately-sold property in the private property database 23 in step S49 shown in FIG.

The recommender server 13 that has registered the new privately-sold property in the private property database 23 first performs the processes of steps S61 and S62 for each record in the condition database 25 (step S60). Specifically, it is determined whether or not the newly registered privately-sold property meets the desired conditions indicated by the attention record (step S61), and if it is determined that the conditions are met, the corresponding condition ID and the property ID for sale are determined. Is registered in the distribution database 26 (step S62). At this point, the date in the newly registered record is blank.

The recommender server 13 that has completed the iterative process of step S60 subsequently performs the processes of steps S64 to S68 for each record whose date has not been entered registered in the distribution database 26 (step S63). Specifically, the recommender server 13 first reads the member ID corresponding to the condition ID from the condition database 25 (step S64), and reads the address information corresponding to the read member ID from the member database 24 (step S65). .. Subsequently, the recommender server 13 generates a distribution page including information on the property stored in the private property database 23 in association with the property ID for sale (step S66). Then, the distribution page generated in step S66 is transmitted to the address information read in step S65 (step S67), the current date is set as the date in the distribution database 26 (step S68), and the processing for the record is performed. To finish. The recommender server 13 that has completed the iterative process of step S63 ends the distribution process.

FIG. 15 is a diagram showing a distribution page 53, which is an example of the distribution page generated in step S66. As shown in the figure, the distribution page 53 is a page including various information of the property for sale that is the target of distribution. The recommender server 13 generates this distribution page 53 by reading information from the private property database 23.

As shown in FIG. 15, a graph area 53a showing the profitability of the property for sale is arranged on the distribution page 53. The recommender server 13 is configured to generate information to be displayed in the graph area 53a based on the price and deviation values stored in the property database 22 and the private property database 23. Hereinafter, it will be described in detail.

First, the deviation value will be explained. When the recommendation server 13 generates the distribution page 53, the property similar to the property for sale to be distributed (the property for sale stored in the property database 22 and the private property database 23) The stored property for sale and at least one of the rental properties stored in the rental property database 22) are extracted from the property database 22 and the private property database 23. Criteria for determining similar properties include, for example, address (whether or not they are in the same ward), nearest station (whether or not the nearest station is the same), occupied area (whether or not the difference in occupied area is within a predetermined value), and location. The floor (whether the floor is the same or not), the balcony direction (whether the same direction or not), etc. may be used.

The recommender server 13 that extracts similar properties obtains the average value and variance of the prices of the extracted properties. The price used here may be acquired or estimated in the same manner as in step S32 of FIG. The recommender server 13 calculates a price deviation value for each of the sales property to be distributed and the extracted similar property using the calculated average value and variance, and stores the value in the property database 22 and the private property database 23. The deviation value calculated in this way is information indicating the profitability of each property for sale in the similar property group.

The recommender server 13 generates a curve graph (for example, a normal distribution curve) based on the calculated mean value and variance, and draws it in the graph area 53a (the illustrated "price distribution"). In addition, these sales properties are plotted on a normal distribution curve based on the deviation values of the sales properties to be distributed and the extracted similar properties. At this time, as illustrated in FIG. 15, the recommender server 13 uses markers having different shapes for the property to be distributed, the similar property that has not been contracted, and the similar property that has been contracted. As a result, the user can intuitively know the profitability of the property to be distributed in the similar property group.

FIG. 16 is a sequence diagram of a part of the sale property registration process and the distribution process (up to the registration in the distribution database 26) executed by the members market server 12 and the recommender server 13. Further, FIG. 17 is a sequence diagram of the rest of the member registration process, the desired condition registration process, and the distribution process executed by the recommender server 13. Hereinafter, by referring to FIGS. 16 and 17, the processing performed by the members market server 12 and the recommender server 13 will be described from another viewpoint.

First, referring to FIG. 16, the member's market server 12 first receives information on the property for sale from the user terminals 30 and 31 of the user who is the seller (step S120). Then, it is determined whether or not the user wants to be private (step S121), and if the user does not want to be private, it is registered in the property database 22 (step S122), while the user wants to be private. In that case, the information of the property for sale is transferred to the recommender server 13 (step S123).

The recommender server 13 that has received the transfer of the property information for sale registers the information in the private property database 23 (step S124), and extracts the desired conditions that match the registered property information for sale from the condition database 25 (step). S125), the combination of the extracted condition ID of the desired condition and the sales property ID of the registered sales property information is registered in the distribution database 26 (step S126).

Next, referring to FIG. 17, at the stage of first registering the member, the recommender server 13 receives personal information from the user terminals 30 and 31 of the user who is the buyer of the privately-sold property (step S130), and is in charge of the examination. After having a person perform the examination (step S131), the person is registered in the member database 24 (step S132). The examination in step S131 is an examination as to whether or not the user is sufficient to be registered as a good buyer, and if the examination result that the user is not sufficient to be registered as a good buyer is obtained, the examination in step S132 is executed. Not done.

Next, at the stage of registering the desired conditions, the recommender server 13 first authenticates whether or not the user of the user terminals 30 and 31 is a member registered in the member database 24 (step S133). Then, when the member is authenticated, the information indicating the desired condition is received from the user terminals 30 and 31 of the user (step S134), and the information is registered in the condition database 25 (step S135). The member authentication in step S133 may be, for example, authentication by a member ID and a password.

Finally, at the stage of executing the distribution of the sales property information, the recommender server 13 first acquires the combination of the condition ID and the sales property ID from the distribution database 26 (step S140). Then, the member ID corresponding to the condition ID is acquired from the condition database 25 (step S141), and the address information corresponding to the acquired member ID is acquired from the member database 24 (step S142).

Next, the recommender server 13 reads the information of the property ID for sale acquired in step S140 from the private property database 23 (step S143), and generates a distribution page based on the read information (step S144). The specific contents of the distribution page are as described above. After that, the recommender server 13 transmits the distribution page generated in step S144 to the address information acquired in step S142 (step S145), and ends the process.

As described above, according to the members market server 12 and the recommender server 13 according to the present embodiment, the information of the privately-sold properties is registered in the private property database 23 different from the property database 22. Since information on properties for sale that meet the desired conditions is distributed to buyers who are allowed to register the desired conditions in the condition database 25 in advance, sales that can give preferential treatment to good buyers and attract good buyers. It will be possible to provide a site.

The recommender server 13 according to the present embodiment starts the distribution process shown in FIG. 12 in response to the registration of the privately-sold property in the private property database 23 in step S49 shown in FIG. The distribution page containing the information of the privately-sold property stored in the public property database 23 was distributed, but it is shown in FIG. 12 in response to the registration of the publicly-sold property in the property database 23 in step S45 shown in FIG. The distribution process may be started and the distribution page including the information of the publicly-sold property stored in the property database 23 may be distributed, or both of them may be executed. When distributing the distribution page including the information of the publicly-sold property, the recommender server 13 determines in step S61 whether or not the newly registered publicly-sold property meets the desired conditions indicated by the attention record, and matches. If so, in step S62, the combination of the corresponding condition ID and the property ID for sale may be registered in the distribution database 26. Further, in step S66, the recommender server 13 may generate a distribution page including information on the property stored in the property database 22 in association with the property ID for sale.

Although the preferred embodiments of the present invention have been described above, the present invention is not limited to these embodiments, and the present invention can be implemented in various embodiments without departing from the gist thereof. Of course.

For example, in FIG. 1, the property database 22 and the private property database 23 are drawn separately, but these may be integrated into one database. In this case, in order to make it possible to distinguish between the publicly-sold property and the privately-sold property, it is preferable to set a public availability flag in each record, for example.

Further, in the above embodiment, the example in which only the excellent buyers are registered in the member database 24 has been described, but users other than the excellent buyers may also be able to register as members. In this case, by setting a flag in the member database 24 to identify whether or not the buyer is a good buyer, the registration of the desired conditions is permitted only to the good buyer, and the private sale property information is distributed. good.

1 Information processing system 2 Sales site 3 Network 10 Information processing equipment 11 Planner server 12 Members market server 13 Recommender server 20 Mansion database 21 Rental property database 22 Property database 23 Private property database 24 Member database 25 Condition database 26 Distribution database 30, 31 User terminal 40, 43, 51, 52 Information input page 40a Property name input field 40b Rent input field 40c Input field 40d Location floor input field 40e Square room button 40f South facing button 40g Remodeled button 40h, 51a, 52a Transition button 41 , 42 Information output page 50 Publication type selection page 50a, 50b Selection button 53 Distribution page 53a Graph area 101 Processor 102 Storage device 103 Communication device 104 Input device 105 Output device 106 Bus

Claims (8)

Based on the input rental property information, which is the rental property information input by the first user, one or more properties are extracted from the database that stores the information of multiple properties.
Information indicating each of the extracted one or more properties is output to the first user.
Information processing equipment. Estimate the appropriate purchase price of the rental property indicated by the input rental property information,
The above-mentioned one or more properties are sales properties that can be purchased at a price difference within a predetermined value from the estimated appropriate purchase price.
The information processing apparatus according to claim 1. One or more neighborhood-like properties that are located in the vicinity of the rental property indicated by the input rental property information and are similar to the rental property are extracted from the database.
Based on the price and rent of each of the one or more neighboring similar properties, the average value of the yields of the one or more neighboring similar properties is calculated.
Of the rental properties stored in the rental property database that stores information on multiple rental properties, one or more neighborhood-like rentals that are located in the vicinity of the rental property indicated by the input rental property information and that are similar to the rental property. Based on the rent of each property and the average value of the yield, the price of each of the above 1 or more similar rental properties in the neighborhood is estimated.
The appropriate purchase price is an average value of the estimated prices of one or more neighboring similar rental properties.
The information processing apparatus according to claim 2. Based on the estimated appropriate purchase price, the loan repayment amount when the user purchases the rental property indicated by the input rental property information is calculated, and the calculated loan repayment amount is output to the first user. ,
The information processing apparatus according to claim 2 or 3. Among the rental properties stored in the rental property database that stores the input rental property information and the information of a plurality of rental properties, the rental property is located near the rental property indicated by the input rental property information and is similar to the rental property. The rent of each of the one or more neighborhood-like rental properties is corrected based on the information of each of the one or more neighborhood-like rental properties, and the average value of the rent of each of the one or more neighborhood-like rental properties after the correction is calculated as described above. Output to the first user as the appropriate rent of the rental property indicated by the input rental property information.
The information processing apparatus according to claim 1. The database is a property database that stores information on a plurality of properties for sale.
According to the selection of the second user who is the seller, the information of the property for sale input by the second user is stored in the property database or the private property database for storing the information of a plurality of private properties for sale. Register on one side,
The information processing apparatus according to any one of claims 1 to 5. A step of extracting one or more properties from a database that stores information of a plurality of properties based on the input rental property information that is the rental property information input by the first user.
A step of outputting information indicating each of the extracted one or more properties to the first user, and
Information processing methods including. A step of extracting one or more properties from a property database that stores information on multiple properties based on the input rental property information that is the rental property information input by the first user.
A step of outputting information indicating each of the extracted one or more properties to the first user, and
A program that lets your computer run.

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