WO2004027668A1 - 不動産共同購入マッチングシステム - Google Patents
不動産共同購入マッチングシステム Download PDFInfo
- Publication number
- WO2004027668A1 WO2004027668A1 PCT/JP2003/011991 JP0311991W WO2004027668A1 WO 2004027668 A1 WO2004027668 A1 WO 2004027668A1 JP 0311991 W JP0311991 W JP 0311991W WO 2004027668 A1 WO2004027668 A1 WO 2004027668A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- real estate
- purchase
- information
- property
- customer
- Prior art date
Links
- 238000000605 extraction Methods 0.000 claims abstract description 24
- 238000004891 communication Methods 0.000 claims abstract description 4
- 238000012545 processing Methods 0.000 claims description 20
- 230000008450 motivation Effects 0.000 claims description 3
- 238000013500 data storage Methods 0.000 claims 3
- 230000007613 environmental effect Effects 0.000 claims 1
- 238000010586 diagram Methods 0.000 description 11
- 230000000694 effects Effects 0.000 description 9
- 239000000284 extract Substances 0.000 description 9
- 238000000034 method Methods 0.000 description 7
- 230000005540 biological transmission Effects 0.000 description 6
- 230000008859 change Effects 0.000 description 4
- 230000008569 process Effects 0.000 description 4
- 229930091051 Arenine Natural products 0.000 description 1
- 101000911772 Homo sapiens Hsc70-interacting protein Proteins 0.000 description 1
- 230000001174 ascending effect Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000005192 partition Methods 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 238000009966 trimming Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/16—Real estate
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
- G06Q40/02—Banking, e.g. interest calculation or account maintenance
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/16—Real estate
- G06Q50/167—Closing
Definitions
- the present invention relates to a real estate joint venture that allows a prospective real estate purchaser to register the condition information desired by Kita using a data communication network and purchase a real estate property that meets the desire in a short period of time.
- FIG 13 is a diagram showing the flow of conventional real estate sales.
- Real estate sale applicant 1 requests real estate purchase broker 2a to broker the sale of its real estate property.
- the real estate purchase broker 2a provides information to the group to which it belongs as a distribution property.
- the real estate purchase broker 2a negotiates with the condominium owner 3 who wants to purchase the real estate. After the contract is concluded, the condominium owner 3 designs and plans and sells it as a condominium house through the agency of the real estate sales intermediary 2b.
- the real estate sales intermediary 2b recruits prospective buyers 4 by registering it in the property database 5 to which it belongs.
- Real estate buyers 4 A desired property is searched for from among the real estate properties registered in the property database 5 to which the agent 2b belongs. If there is a property that meets the purchase conditions of the real estate purchase applicant 4, the real estate sales intermediary 2b negotiates the purchase price, etc., and the real estate sales business owner 3 and the real estate purchase applicant 4 make a sales contract.
- Property database 5 is a general Internet for making contracts between sellers and buyers. ⁇ ⁇
- real estate purchase brokers may register real estate properties they wish to sell in the property database, but access the property database installed in a limited range of distribution facilities from real estate purchasers. It is infrequent and difficult to sell early.
- real estate procurement intermediaries had the problem that the contract closing rate per prospective real estate purchaser was poor, and it took a lot of time and effort to complete the contract.
- the present invention enables a person who wants to sell real estate to efficiently find a property that meets various purchase conditions without trial and error of a search.
- Real estate that can sell real estate properties in a short period of time has a good closing rate per customer for real estate purchase brokers and real estate sales brokers, and saves a lot of time and labor until contract conclusion
- the purpose is to obtain a joint purchase matching system.
- the real estate joint purchase matching system of the present invention is a A search condition setting means for analyzing desired conditions and purchaser attribute information and setting conditions for searching for a purchaser who roughly corresponds to the desired condition is provided, and the search conditions set by the search condition setting means include items for each item.
- the priority priority degree of the condition is quantified, and the real estate purchase applicant information connected to the network is registered by setting search conditions with a certain range for the numerical value of each item.
- the real-estate joint purchase matching system analyzes real-estate purchase applicant condition information and real-estate purchase applicant attribute information in which the purchase applicant information of the real estate purchase applicant is described in natural language by the purchase applicant.
- the real estate purchase applicant storage means stores real estate purchase applicant information described in a natural language, and numerical values of importance ranking are described in respective items. Things. If it is not described, the content of the description in the natural language is analyzed, the content indicating the importance is analyzed, and the priority order of the purchaser's desired condition is determined. Further, in the real estate joint purchase matching system according to the present invention, the real estate purchase applicant storage means uses the priority importance level numerical value when the purchase request condition has a priority importance level numerical value, and uses the priority importance level numerical value. If no numerical value is given, the priority importance degree value determined by the real estate purchase candidate summary extraction means determined by analyzing the purchaser condition is used to determine the priority importance value of the purchase condition. .
- the real estate joint purchase matching system provides a real estate purchase by a search condition setting means corresponding to each of the arbitrarily set real estate in the purchase applicant information database organized by the real estate purchase applicant summary extracting means.
- a database of applicants for purchase of real estate is selected from among the plurality of candidates for purchase of real estate extracted by the extraction means for real estate purchase applicants.
- the real estate purchase applicant summary extraction means of the real estate joint purchase matching system includes information on whether the desired real estate is land or housing with land, desired railroad information, desired station information, desired real estate Priorities for pricing information A system is provided for digitizing.
- the real estate purchase applicant summary extraction means of the real estate joint purchase matching system includes: name, age, current address, telephone number, e-mail address, family structure, occupation and place of employment and the length of service, annual income, and down payment. It has a system that can be used as a numerical value as a degree of attribute condition, including the presence / absence, motivation to enter, the current dwelling ability of the house, and whether or not.
- the real estate joint purchase matching system has a search condition setting means for analyzing information of a real estate property database, quantifying its priority, and setting search conditions for a corresponding real estate purchase applicant. It is.
- FIG. 1 is a block diagram showing a configuration of a real estate joint purchase matching system according to an embodiment of the present invention
- FIG. 2 is a flowchart showing a processing flow of the real estate joint purchase matching system according to one embodiment of the present invention
- FIG. 3 is a diagram for explaining the flow of a database of real estate purchase applicants according to the real estate joint purchase matching system according to one embodiment of the present invention
- FIG. 4 is a view for explaining a flow of a database of applicants for selling real estate related to the real estate joint purchase matching system according to one embodiment of the present invention
- Figure 5 shows a real estate trading system that includes a preferred example of real estate property processing means. Schematic configuration diagram
- Figure 6 shows an example of the input screen used in the real estate trading system of Figure 5;
- Figure 7 is a diagram showing an example of the division pattern used in the real estate trading system of Figure 5;
- Fig. 8 (a) to (c) are diagrams for explaining the division in the real estate trading system of Fig. 5;
- Fig. 9 is a flowchart for explaining the procedure of the real estate trading system in Fig. 5;
- Fig. 10 is a graph showing an example of the distribution of the number of applicants for a property for sale used in the real estate trading system of Fig. 5;
- Fig. 11 is a graph showing another example of the distribution of the number of applicants for the property for sale used in the real estate trading system of Fig. 5;
- Figure 12 is a diagram showing how the 3D image of the building fluctuates as the boundaries of the division change
- FIG. 13 is a diagram for explaining a conventional real estate buying and selling procedure.
- FIG. 1 shows the details of a real estate joint purchase matching system according to an embodiment of the present invention. It is a block diagram showing composition.
- 1 is a candidate who sells properties such as owned real estate
- 2 is a real estate purchase broker who handles the properties that the seller wants to sell
- 3 is a real estate sales broker who handles the properties of the buyer
- 4 is a broker
- 7 is a property database that registers properties that a prospective seller 1 wants to sell
- 6 is an information network. It is assumed that the network 6 is connected to a plurality of real estate property applicants 1, real estate purchase brokers 2, real estate sales brokers 3, and real estate property buyers 4, respectively.
- reference numeral 5 denotes the system.
- This system 5 searches for the properties that the real estate sales broker 3 and the real estate purchaser 4 want directly through the network 6, and sells the real estate properties.
- This is a property search device that can match the information of applicant 1 and real estate purchase broker 2.
- 9 is transmitted via the network 6 and prepared by the real estate purchaser database storage means, and the real estate sales broker 3 and the real estate purchaser 4 described in natural language And a purchase applicant attribute information database.
- Reference numeral 7 denotes a real estate property database for sale, which is transmitted in the network 6 and prepared by the real estate property database storage means, and written by the real estate property applicant 1 and the real estate purchase broker 2 in natural language. .
- Numeral 10 denotes search condition setting means for numerically searching for the superiority of the property and setting the conditions.
- the search condition setting means set by quantifying the priority of the conditions of each item Yes, it is a means to set search conditions with a certain range by changing conditions into constants and variables.
- Reference numeral 11 denotes a real estate purchase applicant outline extraction unit that roughly extracts a plurality of real estate purchase applicants based on an extended search condition in which the search condition set by the search condition setting unit 10 has a certain width.
- 1 and 2 is a desired condition analysis means for setting and combining a plurality of narrowed down property purchase applicants by analyzing the outline of the real estate purchase candidate extraction means.
- a plurality of purchase candidates 13 is a plurality of purchase candidates grouped by 12 corresponding to an arbitrary 7 n.
- a plurality of property databases 7 are accessed via the network 6 and a plurality of real estate are selected from the registered real estate purchase applicants for the properties set for each property by the search condition setting means 10.
- This is a device that extracts joint purchasers 13 and combines them by means of desired condition analysis means 12 so as to meet their needs and performs matching.
- the joint purchase matching device 5 14 is again analyzed by the desired condition analysis means 1 2 for each condition of the plurality of real estate purchase applicants 3 to meet the wish of the joint purchase real estate purchase summary candidate.
- the desired condition analysis means 1 2 for each condition of the plurality of real estate purchase applicants 3 to meet the wish of the joint purchase real estate purchase summary candidate.
- FIG. 2 is a flowchart showing a processing flow of the real estate joint purchase matching system according to the first embodiment of the present invention.
- the party receiving the information by transmitting the desired condition and attribute information of the purchaser analyzes and organizes the contents in 9b, and makes it into the real estate purchaser information database of 9.
- the search condition corresponding to the selected real estate 7 n is selected, and a plurality of prospective candidates for real estate purchase are selected according to the search condition by an analysis that is further narrowed down by the 11 real estate purchase candidate summary extracting means.
- the real estate property information for sale 7a is received by transmitting the property information from the applicant for sale of the real estate, and it is arranged and analyzed in 7b to obtain a real estate sale applicant information database 7.
- Real-estate property applicants selected arbitrarily from the real estate sale applicant information database 7 Real estate of 7 n will be grouped as a candidate for a purchase summary.
- the real estate property processing means 14 jointly purchases real estate by processing the real estate 7 n so that the desired condition analysis means 12 matches the desired conditions of the purchase summary candidates for multiple real estates 7 n. In a short period of time, we will conclude a sale and purchase of real estate 7 n.
- the above is the basic flow of the real estate joint purchase matching system.
- a purchaser of real estate transmits desired purchase conditions and customer information for a desired property to the system device 5 via the network 6.
- the prospective buyer 3 does not describe the purchase conditions and customer information in a specific format, but in a natural language text such as an e-mail.
- FIG. 3 shows the flow of the contents described by the real estate purchase applicant 3.
- whether the land is sought in Step ST 1 Indicate whether you are looking for a housing with attached property, and add the importance to the number from the most important one to 1, 2, 3, and 4 sequentially.
- Step ST2 describes the desire for the desired way.
- the importance is annotated with a number from 1 to 4.
- a description is made to annotate the importance with a number from 1 to 4.
- T 4 describes the selling price of the property.
- T5 describes the house area and floor plan.
- step ST6 the purchase conditions described in step ST6 include the location of the property, information on facilities such as hospitals, nursery schools and kindergartens, and information on the existence of convenience in life such as supermarkets 'school' banks. Information on the presence or absence of facilities that do not want to exist near the garbage disposal site, etc.
- step ST7 of describing the property purchase applicant attribute information the name and age, family structure and age of the property purchase applicant are described.
- Step ST8 describes the current address, telephone and e-mail address.
- T9 describes occupation, place of employment, and years of service.
- T10 describes information such as annual income, down payment for property purchase, and financial institutions.
- step ST11 the motivation to purchase a real estate property In this case, it is described whether the current house is owned by the owner.
- Step ST13 processes as necessary to describe other attribute information.
- Figure 4 shows the flow of the contents described by the real estate seller 1.
- the use and type information of the property to be sold is described in step ST14 as described above.
- step ST15 the location of the property is described.
- step ST16 the owner information of the property is described.
- ST 17 describes the current unit price information of the land and the selling price.
- ST 18 describes the environment etc. related to the location of the property.
- the format will be used in parallel with the format in which the desired purchase conditions and customer information can be linked to the real estate property database.
- real estate purchaser input means 16 analyzes the natural language description contents that describe the order of high importance 1 to 4 for purchase wish conditions described in natural language. The content indicating the degree is described again in a specific format, the change importance is determined, and the grouping search condition is set. For this reason, the customer can safely describe the desired property purchase conditions in the specified columns and express them in ordinary sentences.
- the real estate purchaser summary setting means 1 1 is analyzed and grouped from the purchase request conditions in the real estate purchase applicant database based on the grouping search conditions corresponding to the property 7 n set by the search condition setting means 1 ⁇ . Is converted to a predetermined format and stored in the real estate purchase hopeful catchers group information database 17 in Fig. 2 as real estate purchase applicant information.
- a plurality of candidates for purchase of real estate stored in the candidate information for purchase of real estate by group are analyzed in detail by the desired condition analysis means 12 and the real estate sold by the search condition setting means 10.
- the property information is converted into a format that can be compared with the data of multiple candidates to purchase jointly, linked to the setting of the candidate for real estate purchase corresponding to 7 n arbitrarily set from the property information.
- the desired condition analysis means 12 uses the importance ranking determined by the real estate purchase applicant summary extraction means 11, and further, if no importance ranking has been assigned, the real estate purchase applicant summary extraction If the means 11 cannot determine the order of importance, the priority is determined based on the order of description of the desired purchase conditions described.
- the desired condition analysis means 12 examines a separate request according to, for example, a customer's desired purchase condition.
- a plurality of real estate purchase outline candidate information 13 selected by the desired condition analysis means 12 is expanded by adding a certain width to the analysis conditions set by the desired condition analysis means 12.
- the applicants registered in the candidate information for prospective real estate grouped by the real estate purchase candidate summary extraction means 11 Strength ⁇ Combine and extract multiple general candidates.
- the real estate purchaser summary extracting means 11 is based on the search conditions set by the search condition setting means 10 and the expanded search conditions having a certain width. A plurality of candidates are extracted by analyzing desired conditions.
- the real estate property processing means 14 is a search condition setting means 10, a real estate purchase applicant summary extracting means 11, and the desired conditions of a plurality of purchase applicants set by the applicant summary extraction means are analyzed and arbitrarily determined. This is a means by which the real estate property corresponding to the property 7 n set in the above can be processed to match the desired conditions of each purchaser as much as possible, so that each purchaser can purchase jointly. It is a new tool that enables
- the real estate property processing means 14 notifies a plurality of confirmed general candidates via the network 5.
- a prospective real estate purchaser 4 pays a brokerage commission to a real estate agent 3 upon closing. This is in return for the prospective real estate purchaser 3 having purchased a property that meets their wishes.
- the real estate agent 2 and the real estate agent 3 pay a success fee to the real estate joint purchase matching system administrator 5. This is a price for the increase in the efficiency of the brokerage business by treating the real estate agent 2 and the real estate agent 3 who are likely to become real estate buyers 1.
- the real estate purchase applicant 4 efficiently finds a property that meets various desired purchase conditions without performing trial and error in property search.
- this system search device analyzes the purchase request conditions and customer attribute information described by the real estate purchase applicant, organizes them into the set format, and searches the real estate sale applicant information database using the search condition setting means. Select the search condition corresponding to the arbitrarily selected real estate property n, and access multiple real estate purchase applicants from the real estate purchase applicant database according to the search condition, and select from the registered real estate purchase applicants According to the numerical value of the importance of the requirement of the real estate purchase applicant, the real estate purchase applicant summary extracting means groups the buyers of the outline. For the candidate who wishes to purchase the real estate, the purchase conditions and customer attribute information are searched in detail, and the purchase condition candidates are grouped by the request condition analysis means for narrowing down the candidate purchase candidates.
- the grouped candidates are linked with the real estate property processing means and have the effect of being able to purchase properties that match the desired conditions in a short period of time.
- real estate property processing means that determines the candidate properties desired by each purchaser and notifies the real estate purchase applicant is provided, so that the real estate purchaser can perform trial and error in searching for properties. Without having to search for properties that meet various conditions of purchase, efficiently, and for those who want to sell real estate, it is possible to quickly sell the properties they want to sell, and for real estate agents to purchase real estate. Rare It has a good closing rate per candidate, and can save a lot of trouble and time until a contract is signed.
- Real estate buyers can efficiently find properties that meet various purchase wish conditions without trial and error in property search, and real estate buyers can find properties they want to sell. It is possible to sell at an early stage, real estate agents have a good closing rate per real estate purchaser, can save a lot of time and effort until the contract is concluded, and the real estate purchaser can get information quickly This has the effect that real estate distribution processing can be performed more efficiently.
- the customer condition analysis means analyzes the purchase condition and customer information described in natural language by the customer, so that the customer can express the purchase condition in ordinary sentences without having to know a specific format. There is an effect that can be.
- the search condition setting means of the real estate purchase applicant does not specify the order of importance for the purchase request condition described in natural language
- the content of natural language is analyzed and the purchase is performed based on the content indicating the importance level.
- search condition setting means ranks the desired purchase conditions in the order of importance, the order is used, and if not, the importance determined by the search condition setting means is determined. If the real estate purchase applicant summary extraction means cannot determine the importance ranking using the ranking, By deciding the priority of the desired purchase conditions, there is an effect that the customer can express the desired purchase conditions in ordinary sentences without being conscious of a specific format.
- the business owners can reduce the risk of sales, and can increase profits by using capital effectively.
- FIGS. 5 to 12 show preferred specific examples including the real estate property processing means.
- FIG. 5 is a diagram showing a schematic configuration of a real estate trading system.
- the real estate trading system shown in FIG. 5 includes a real estate trading management center 40.
- the real estate transaction management center 40 is connected to a customer (applicant for real estate purchase) 43 and a real estate agent 42 having real estate for sale via a network 41 such as the Internet. Therefore, the customer 43 registers the customer information with the real estate sales management center 40 via the network 41, and the real estate sales management center 40 stores the information of the property desired by the customer (partition pattern, Price, etc.) to the customer 43 via the network 41. Further, the real estate agent 42 provides the information on the property to be sold to the real estate transaction management center 40 via the network 41.
- the real estate sales management center 40 has a customer data update section 101, a customer database (customer DB) 102, a property data update section 103, a property database (property DB) 104, and applicants.
- Extraction unit 105 division pattern database (pattern DB) 106, division pattern selection unit 107, price range check unit 108, division pattern / price determination unit 109, data transmission and reception
- the main part is composed of
- the data transmission / reception unit 110 receives property data such as a property to be sold from the real estate agent 4 2 ⁇ ⁇ customer data from the customer 4 3 via the network 41, as well as the real estate sales management center 4 0
- the information such as the division pattern and the price determined in the above is transmitted to the customer 43 via the network 41.
- the customer data updating unit 101 receives the data input on the site by the customer 43 and writes the data to the customer DB 102.
- the customer data updating unit 101 manages the customer data of the customers 43 registered in the present system. Specifically, for example, on the input screen on the site as shown in Fig. 6, the property type, desired railroad station, station, budget (preferred price), floor plan, person in charge, personal information (address, name, age, Occupation, phone number, etc.).
- the customer DB 102 data input on the site for each customer is stored based on the input data.
- the property data updating unit 103 receives property data such as a sale property entered on the site by the real estate agent 42 and writes the property data to the property DB 104. As a result, the property data update section 103 can update the property data provided by the real estate to manage.
- property data we use properties that are easily trimmed (formed into rectangles) and are trimmed (shaped) in advance (see Fig. 8). Therefore, data such as frontage and depth in the state of being trimmed in a rectangular shape is used as property data. This trimming process may be performed manually by input means (not shown) or automatically by the property data updating unit 103. Alternatively, the property data in a state in which the real estate agent 42 has trimmed in advance may be transmitted.
- the applicant extracting unit 105 extracts a customer who wants a property from the customer DB 102 based on the property data from the real estate agent 42.
- the applicant extractor 105 extracts from the customer DB 102 the customers who have listed the railroad or station of the property provided by the real estate agent 42 as the desired railroad / station.
- all customers who list the railroad or station of the property to be provided along the desired railroad-station may be extracted, and the maximum number of extractions is set in advance so that only a predetermined number of customers are extracted. May be.
- the number of customers is limited to a predetermined number, the number of customers registered in the present system may be extracted in ascending order, or may be extracted based on other information such as price.
- the price range checking unit 108 extracts a price range desired by a predetermined number or more of the customers extracted by the applicant extracting unit 105. In other words, the price range check unit 108 obtains a desired price distribution from the customer database 102 and extracts a price range with a large number of customers from the distribution. Then, we check the distribution trend of this price range. Specifically, do you have a large number of customers with a specific desired price? Check if there are any customers. Then, the price range check section 108 sends the check result to the division pattern selection section 107 as information for selecting a pattern. In other words, the price range check unit 108 obtains pattern selection reference information (check result) for selecting a division pattern of the provided property.
- the price range desired by a predetermined number or more of customers is extracted, and the distribution of the extracted price range information is used as the pattern selection reference information.
- the division pattern selection unit 107 described later can select the division pattern. If, the pattern selection criterion information is not limited to this.
- the pattern selection reference information may be obtained in consideration of the surrounding environment such as the direction and the sunshine.
- the division pattern selection unit 107 selects a division pattern from the division pattern database 106 based on the extracted information on the number of applicants and the price range of the applicant.
- the division pattern shown in FIG. 7 can be considered, and is stored in the division pattern database 106 in advance. Assuming that each section meets the requirement of facing the road, the pattern shown in Figure 7 can be considered. In FIG. 7, only patterns up to four sections are listed, but patterns of five or more sections are also stored in the section pattern database 106.
- the pattern can be configured by combining the two-section pattern and the three-section pattern. As described above, the pattern of five or more sections is configured by combining a plurality of section patterns.
- Sectioning pattern ⁇ Price determination section 109 is selected by sectioning pattern selection section 107 Based on the extracted pattern information, the applicant extracted by the applicant extraction section 105, and the price range information extracted by the price range check section 108, matching between the customer and the section is performed. I do. Then, the division pattern 'price determining unit 109 sends the determined information (block, price, etc.) from the data transmitting / receiving unit 110 to the customer 43 via the network 41 when the matching is performed.
- a customer whose location of the provided property is desired is extracted, and pattern selection reference information is obtained based on the extracted distribution of the desired price of the customer.
- the division pattern of the provided property is selected, and the division information is provided to the extracted customers based on the division pattern, the pattern selection reference information, and the customer information.
- the properties to be provided can be matched with the desired conditions, and matching can be achieved. Therefore, it is possible to quickly find a property that meets the desired conditions, and to proceed with a real estate sales contract at an early stage. As a result, it is possible to quickly and efficiently match real estate for sale and real estate purchase applicants.
- FIGS. 8 (a) to 8 (c) are diagrams for explaining divisions in the real estate trading system according to one embodiment of the present invention.
- FIG. 9 is a flowchart for explaining the procedure of the real estate trading system according to one embodiment of the present invention.
- FIG. 10 and FIG. 11 are graphs showing the distribution of the number of applicants for a property for sale used in the real estate trading system according to one embodiment of the present invention. This will be described with reference to the flowchart of FIG.
- the real estate agent 42 provides a property (land for sale). This property information is sent from the real estate agent 42 to the data transmission / reception unit 110 of the real estate trading management center 40.
- the data transmission / reception unit 110 sends the property information to the property data update unit 103.
- the property data updating unit 103 stores the property information in the property database 104. At this time, the property is updated by the property data updating unit 103. That is, when the property shown in FIG. 8 (a) is provided, the property data updating unit 103, as shown in FIGS. 8 (b) and (c), forms a rectangular shape so that the division is easy. (White part) is trimmed. Further, the property data updating unit 103 sends the property information to the applicant extracting unit 105.
- step S105 the applicant extracting unit 105 extracts customers who want to provide the property. That is, the applicant extraction unit 105 extracts customers (target customers) whose desired railways and stations are located along the desired property from the customer database 102. Specifically, the station along the route along the station included in the property information and the station along the route along the customer information stored in the customer database 102 are collated, and all matching customers are extracted. The extracted information of the customer (applicant) is sent to the price range check section 108, the division pattern selection section 107 and the division pattern 'price determination section 109.
- the price range checker 108 checks a price range having a predetermined number or more customers. For example, in the price range tick section 108, the distribution of the desired price of the customer who wants the offer is examined. Specifically, the price range check section 1 08 examines the distribution based on the desired price included in the customer information. The result is, for example, as shown in FIG. 10 and FIG. In Figure 10, only customers with a desired price of 3,500,000 yen stand out, and in Figure 11, three hundred thousand yen, three hundred thousand yen, three hundred thousand yen, and four hundred thousand Many customers use yen as their desired price.
- step S115 the price range check unit 108 determines the tendency of the distribution of the desired price. Specifically, it determines whether the desired price is concentrated on a specific price or not.
- the desired price is concentrated on a specific price, that is, if the distribution is as shown in Fig. 10, in step S120, the number of customers extracted and the minimum sectional area (50 square meters) Determine the number of divisions. For example, in Fig. 10, there are nine customers with a desired price of 3,500,000 yen, so they are equally divided into three groups of three.
- the price range checker 108 uses the pattern selection criterion information to obtain information on the distribution tendency concentrated on a specific price (Fig. 10), the concentrated price, and the number of extracted persons in three groups of three.
- the information is sent to the division pattern selection unit 107 and the division pattern / price determination unit 109 as information.
- the division pattern selection unit 107 selects a division pattern based on the pattern selection reference information.
- the pattern selection criteria information is as follows: distribution: FIG. 10, price: 350,000 yen, group: 3 people, 3 groups, and based on that, Refer to the pattern database 106 to select an even division pattern. Specifically, the area as shown in Fig. 8 (b) Select a split pattern. Then, the information on the division pattern is sent to the division pattern 'price determination unit 109.
- the division pattern and price determination unit 109 determines the division pattern and the price based on the division pattern information, the customer information, and the pattern selection reference information.
- the division pattern / price determination unit 109 functions as the real estate property processing means described above, and even if the real estate property is processed so as to match the wishes of multiple customers (real estate purchase summary advisers). good.
- the division pattern-price determination unit 109 for example, as shown in FIG. , 20 OB may be formed, and the boundary L between the divisions A and B may be varied as shown in FIG.
- the size of the stereoscopic images 20 OA and 20 OB of the building may change as shown in FIG. 12 (b) with the change of the boundary L between the divisions A and B.
- the information on the division and the price is sent from the data transmission / reception unit 110 to the customer 43 via the network 41.
- the provision of the price information may be performed on the network as described above, or may be performed by mail or the like.
- the number of divisions is determined from the number of extracted customers. For example, in Figure 11, three customers have a desired price of 30 million yen, five customers have a desired price of 35 million yen, and four customers have a desired price of 40 million yen. There are four people. In this case, the parcels are classified into low-priced parcels, medium-priced parcels, and high-priced parcels. This grade is determined as appropriate in consideration of the surrounding environment such as direction and sunshine. Then, three groups of low-priced parcels (300,000 yen), three persons of medium-priced parcels (350,000 yen), and three persons of high-priced parcels (400,000 yen) are divided.
- the price range check section 1108 is based on the trend of distribution that is not concentrated on a specific price ( Figure 11), multiple prices (300,000, 3,500,000 yen, 4,000,000 yen) ) And information on the number of extracted persons in three groups of three as pattern selection reference information is sent to the division pattern selection unit 107 and the division pattern / price determination unit 109.
- the division pattern selection unit 107 selects a division pattern based on the pattern selection reference information. That is, in the division pattern selection unit 107, the pattern selection reference information is as follows: distribution: FIG. 11, price: 3,100,000 yen, 3,500,000 yen, 4,000,000 yen, group: low Since it is a group consisting of three price parcels, three middle-priced parcels and three high-priced parcels, the division pattern is selected based on the group and referring to the division pattern database 106. Specifically, a division pattern as shown in Fig. 8 (c) is selected. Then, the information on the division pattern is sent to the division pattern 'price determination unit 109.
- the pattern selection reference information is as follows: distribution: FIG. 11, price: 3,100,000 yen, 3,500,000 yen, 4,000,000 yen, group: low Since it is a group consisting of three price parcels, three middle-priced parcels and three high-priced parcels, the division pattern is selected based on the group and
- step S130 the division pattern / price determination unit 109 determines a division pattern and a price based on the division pattern information, customer information, and pattern selection reference information. Then, the information on the division pattern and the price is transmitted from the data transmission / reception unit 110 to the customer 43 via the network 41.
- ward division- The provision of the price information may be performed on the network as described above, or may be performed by mail or the like.
- the customer 4 3 having received the information on the division pattern and the price sends a response as to whether or not to make a purchase to the real estate agent 42 via the real estate transaction management center 40. Thereafter, negotiations on a contract between the real estate agent 42 and the customer 43 begin. In this way of, c It should be noted that it is possible to proceed quickly and efficiently real estate sale and purchase agreement, is one of the answer if you want to purchase, carried out in the form of a reply e-mail that sectioning patterns and price of information is attached May be performed on the site of this system.
- the present invention is not limited to the above embodiment, but can be implemented with various modifications.
- the input items, layout, division pattern, and the like on the input screen on the site are not limited to the above embodiment, and can be variously changed.
- a division pattern is determined in consideration of a price range.
- the division pattern may be determined in consideration of other conditions, for example, the surrounding environment such as direction and sunshine.
- a case is described in which the processing from extraction of a desired person to selection of a division pattern is performed by hardware. May be configured.
- the process from extraction of the applicant to the division pattern is programmed, and the program
- the RAM may be stored in the ROM, and the program may be operated according to the instruction of the CPU according to the program.
- the program may be stored in a computer-readable storage medium, and the program in the storage medium may be recorded in the RAM of the computer, and may be operated according to the program. Even in such a case, the same operation and effect as those of the above embodiment are exhibited.
Landscapes
- Business, Economics & Management (AREA)
- Finance (AREA)
- Accounting & Taxation (AREA)
- Engineering & Computer Science (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Marketing (AREA)
- Theoretical Computer Science (AREA)
- Strategic Management (AREA)
- Physics & Mathematics (AREA)
- Economics (AREA)
- Tourism & Hospitality (AREA)
- Development Economics (AREA)
- Human Resources & Organizations (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Health & Medical Sciences (AREA)
- Technology Law (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
Description
Claims
Priority Applications (3)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
AU2003264522A AU2003264522A1 (en) | 2002-09-20 | 2003-09-19 | Estate group purchasing matching system |
JP2004538000A JP4348419B2 (ja) | 2002-09-20 | 2003-09-19 | 不動産共同購入マッチングシステム |
US10/528,449 US20060167701A1 (en) | 2002-09-20 | 2003-09-19 | Estate group purchasing matching system |
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
JP2002-311870 | 2002-09-20 | ||
JP2002311870 | 2002-09-20 |
Publications (1)
Publication Number | Publication Date |
---|---|
WO2004027668A1 true WO2004027668A1 (ja) | 2004-04-01 |
Family
ID=32025605
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/JP2003/011991 WO2004027668A1 (ja) | 2002-09-20 | 2003-09-19 | 不動産共同購入マッチングシステム |
Country Status (6)
Country | Link |
---|---|
US (1) | US20060167701A1 (ja) |
JP (1) | JP4348419B2 (ja) |
KR (1) | KR20050053674A (ja) |
CN (1) | CN1682230A (ja) |
AU (1) | AU2003264522A1 (ja) |
WO (1) | WO2004027668A1 (ja) |
Cited By (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2005234905A (ja) * | 2004-02-19 | 2005-09-02 | Takenaka Komuten Co Ltd | 住宅販売支援装置、住宅販売支援システム、住宅販売支援方法及び住宅販売支援プログラム |
JP2006221303A (ja) * | 2005-02-09 | 2006-08-24 | S X L Corp | 土地分譲支援システム |
JPWO2005020115A1 (ja) * | 2003-08-26 | 2007-11-01 | 株式会社ニード | 不動産売買システム |
JP2021179844A (ja) * | 2020-05-14 | 2021-11-18 | 株式会社レアル | 情報処理装置、プログラム及び方法 |
Families Citing this family (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN106354758B (zh) * | 2016-08-17 | 2019-08-20 | 北京小米移动软件有限公司 | 处理房屋信息的方法及装置 |
CN107274220A (zh) * | 2017-06-12 | 2017-10-20 | 张和强 | 一种网上定价会员制低买快卖住房方法 |
JP7017330B2 (ja) * | 2017-07-13 | 2022-02-08 | ソフトバンク株式会社 | マッチングコンピュータ、マッチング方法及びプログラム |
CN111539789A (zh) * | 2020-04-24 | 2020-08-14 | 天津市橙桔科技有限公司 | 一种高效房产成交匹配系统 |
TWI832030B (zh) * | 2021-01-08 | 2024-02-11 | 聚英企業管理顧問股份有限公司 | 基於大數據之購屋需求的辨識裝置 |
Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2001256300A (ja) * | 2000-03-09 | 2001-09-21 | Misawa Homes Co Ltd | 不動産情報提供システムおよび不動産情報提供方法 |
JP2002132893A (ja) * | 2000-10-27 | 2002-05-10 | Work Supply:Kk | 不動産情報提供システム |
JP2002259532A (ja) * | 2001-03-01 | 2002-09-13 | Tokyo Misawa Homes Co Ltd | 土地共同購入支援方法,土地共同購入支援装置および土地共同購入支援システム |
Family Cites Families (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5754850A (en) * | 1994-05-11 | 1998-05-19 | Realselect, Inc. | Real-estate method and apparatus for searching for homes in a search pool for exact and close matches according to primary and non-primary selection criteria |
US6418415B1 (en) * | 1996-09-04 | 2002-07-09 | Priceline.Com Incorporated | System and method for aggregating multiple buyers utilizing conditional purchase offers (CPOS) |
CA2397762A1 (en) * | 2000-01-25 | 2001-08-02 | Autodesk, Inc. | Method and apparatus for providing access to and working with architectural drawings on the internet |
WO2004003702A2 (en) * | 2002-06-27 | 2004-01-08 | Geranio Nicholas L | Integrated property database and search engine |
-
2003
- 2003-09-19 CN CNA038222116A patent/CN1682230A/zh active Pending
- 2003-09-19 KR KR1020057004700A patent/KR20050053674A/ko not_active IP Right Cessation
- 2003-09-19 WO PCT/JP2003/011991 patent/WO2004027668A1/ja active Application Filing
- 2003-09-19 US US10/528,449 patent/US20060167701A1/en not_active Abandoned
- 2003-09-19 JP JP2004538000A patent/JP4348419B2/ja not_active Expired - Fee Related
- 2003-09-19 AU AU2003264522A patent/AU2003264522A1/en not_active Abandoned
Patent Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2001256300A (ja) * | 2000-03-09 | 2001-09-21 | Misawa Homes Co Ltd | 不動産情報提供システムおよび不動産情報提供方法 |
JP2002132893A (ja) * | 2000-10-27 | 2002-05-10 | Work Supply:Kk | 不動産情報提供システム |
JP2002259532A (ja) * | 2001-03-01 | 2002-09-13 | Tokyo Misawa Homes Co Ltd | 土地共同購入支援方法,土地共同購入支援装置および土地共同購入支援システム |
Cited By (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPWO2005020115A1 (ja) * | 2003-08-26 | 2007-11-01 | 株式会社ニード | 不動産売買システム |
JP2005234905A (ja) * | 2004-02-19 | 2005-09-02 | Takenaka Komuten Co Ltd | 住宅販売支援装置、住宅販売支援システム、住宅販売支援方法及び住宅販売支援プログラム |
JP2006221303A (ja) * | 2005-02-09 | 2006-08-24 | S X L Corp | 土地分譲支援システム |
JP2021179844A (ja) * | 2020-05-14 | 2021-11-18 | 株式会社レアル | 情報処理装置、プログラム及び方法 |
Also Published As
Publication number | Publication date |
---|---|
CN1682230A (zh) | 2005-10-12 |
KR20050053674A (ko) | 2005-06-08 |
AU2003264522A1 (en) | 2004-04-08 |
US20060167701A1 (en) | 2006-07-27 |
JP4348419B2 (ja) | 2009-10-21 |
JPWO2004027668A1 (ja) | 2006-01-19 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US20210342962A1 (en) | System and method for standardizing and tracking land use utility | |
US20190066241A1 (en) | Methods for transforming complex zoning codes and regulations to produce usable data | |
JP2001357197A (ja) | ポジション表示システム及びコンピュータ可読媒体 | |
KR102647986B1 (ko) | 인공지능 기반 프랜차이즈 컨설팅 시스템 및 방법 | |
Malek et al. | Identification, evaluation, and allotment of critical risk factors (CRFs) in real estate projects: India as a case study | |
JP2002132893A (ja) | 不動産情報提供システム | |
JP7382274B2 (ja) | 出力プログラム、出力方法及び出力装置 | |
JP2003022314A (ja) | 不動産価格関数推定方法、不動産価格関数推定装置、及び不動産価格関数推定プログラム | |
Nase et al. | Urban design quality and real estate value: in search of a methodological framework | |
KR20070056017A (ko) | 상표 시스템 | |
JP6137583B2 (ja) | 要請者のニーズを反映した文化芸術創作物の統合管理サービス提供システムの動作方法 | |
WO2004027668A1 (ja) | 不動産共同購入マッチングシステム | |
US20030144911A1 (en) | System and method for list shopping over a computer network | |
KR20070097939A (ko) | 서버 및 클라이언트 단말기를 이용한 부동산 정보 제공방법 및 이를 수행하는 컴퓨터 프로그램이 기록된컴퓨터에서 판독 가능한 기록 매체 | |
EP1975864A1 (en) | Resource exploitation supporting method, information processing device, and computer program | |
JP2002304555A (ja) | 製品提案方法及びシステム | |
Larraz et al. | A computer-assisted expert algorithm for real estate valuation in Spanish cities | |
JP2002189791A (ja) | 不動産流通システム | |
WO2005020115A1 (ja) | 不動産売買システム | |
KR20200117668A (ko) | 크로스크레딧 기반의 b2b2c 크로스보더 전자상거래 시스템 | |
JPH117468A (ja) | 不動産情報管理システムおよび不動産情報管理方法 | |
JP2008071003A (ja) | シニアライフプランニング支援システム | |
KR20210019906A (ko) | 부동산 통합정보시스템을 이용한 거래 서비스 제공방법 | |
KR101960863B1 (ko) | 기술가치 평가 시스템 | |
Itoh | Estimating the willingness to pay of industrial firms for Japanese industrial parks |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
AK | Designated states |
Kind code of ref document: A1 Designated state(s): AE AG AL AM AT AU AZ BA BB BG BR BY BZ CA CH CN CO CR CU CZ DE DK DM DZ EC EE EG ES FI GB GD GE GH GM HR HU ID IL IN IS JP KE KG KP KR KZ LC LK LR LS LT LU LV MA MD MG MK MN MW MX MZ NI NO NZ OM PG PH PL PT RO RU SC SD SE SG SK SL SY TJ TM TN TR TT TZ UA UG US UZ VC VN YU ZA ZM ZW |
|
AL | Designated countries for regional patents |
Kind code of ref document: A1 Designated state(s): GH GM KE LS MW MZ SD SL SZ TZ UG ZM ZW AM AZ BY KG KZ MD RU TJ TM AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HU IE IT LU MC NL PT RO SE SI SK TR BF BJ CF CG CI CM GA GN GQ GW ML MR NE SN TD TG |
|
121 | Ep: the epo has been informed by wipo that ep was designated in this application | ||
WWE | Wipo information: entry into national phase |
Ref document number: 2004538000 Country of ref document: JP |
|
ENP | Entry into the national phase |
Ref document number: 2006167701 Country of ref document: US Kind code of ref document: A1 |
|
WWE | Wipo information: entry into national phase |
Ref document number: 10528449 Country of ref document: US Ref document number: 1020057004700 Country of ref document: KR Ref document number: 20038222116 Country of ref document: CN |
|
WWP | Wipo information: published in national office |
Ref document number: 1020057004700 Country of ref document: KR |
|
122 | Ep: pct application non-entry in european phase | ||
WWP | Wipo information: published in national office |
Ref document number: 10528449 Country of ref document: US |