JP2017004459A - Real estate transaction system, server, program and recording medium - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a real estate transaction system, server, program and recording medium that calculate a transaction conclusion rate correlated to both of a seller side and a buyer side.SOLUTION: A real estate transaction system 100 comprises: a sellout user terminal 102 including a communication unit and a sellout probability storage unit; a purchase user terminal 103 including a communication unit and a purchase probability storage unit; and a server 101 including a market price storage unit, a lowest successful bid expected price storage unit, a bidding information storage unit, a purchase probability calculation unit, a sellout probability calculation unit, and a bidding number determination unit.SELECTED DRAWING: Figure 1

Description

  The present invention relates to a real estate transaction system, a server, a program, and a recording medium for supporting real estate transactions between a user who sells real estate and a user who purchases real estate.

  Real estate is widely traded not only for residential use but also as a profitable property, that is, an object of investment. Conventionally, in a market where real estate is distributed, it is assumed that information on properties is held by a real estate agent such as an intermediary, and on that basis, mediation of transactions has been performed. For this reason, information for consumers to compare and examine real estate and tools for analyzing real estate have not been sufficiently provided. In addition, when selling real estate for investment, the options have been limited to selling by real estate brokerage or requesting the purchaser to buy, but the seller has information to grasp the appropriate market price of the real estate. There has been a problem that cannot be sufficiently obtained.

  By the way, real estate can be traded by auction through a network, as well as commodities and other movables. In this regard, for example, in Patent Document 1, a virtual auction is executed based on the input property information and virtual bidder information, and a probability distribution of the winning bid price (probability distribution of the expected winning bid price) is calculated. -A technique for graphing is disclosed. Further, for example, in Patent Document 2, a calculation formula using a rental yield, the number of bookmarks, the number of pages viewed, and trust beneficiary rights as a variable regarding a system that supports bidders by predicting how much a successful bid can be made. A technique for calculating a successful bid probability is disclosed.

  However, the technology as described above does not calculate a transaction establishment probability that is correlated with both the seller side and the buyer side, and simply presenting the transaction establishment probability on one side It was hard to say that it contributed to the establishment of the transaction because there was no approach to consciousness. Therefore, there is a need for a technique for promoting transaction by calculating a transaction establishment probability that is correlated with both the seller side and the buyer side.

JP 2008-070917 A JP 2007-164751 A

  The present invention has been made in view of the above circumstances. That is, an object of the present invention is to provide a real estate transaction system, a server, a program, and a recording medium that calculate a transaction establishment probability that is correlated to both the seller side and the buyer side.

  In order to solve the above problems, a real estate transaction system according to the present invention includes a sale user terminal used by a user who sells real estate, a purchase user terminal used by a user who purchases real estate, a sale user terminal and a purchase user. A real estate transaction system comprising a terminal and a server capable of data communication via a network, wherein the selling user terminal transmits property information to the server, receives a market price transmitted from the server, A communication unit that transmits the lowest desired bid price and receives the sale probability transmitted from the server, and a sale probability storage unit that stores the sale probability transmitted from the server. A communication unit for transmitting bid information including at least a bid price to the server and receiving a purchase probability transmitted from the server; A purchase probability storage unit that stores a purchase probability transmitted from the server, and the server includes a market price storage unit that stores a market price according to the property information transmitted from the sale user terminal, and a sale user terminal The purchase probability is calculated using the lowest desired bid price storage unit for storing the lowest desired bid price transmitted, the bid information storage unit for storing bid information transmitted from the purchase user terminal, and the lowest desired bid price and bid price. Purchase probability calculation unit, sale probability calculation unit that calculates the sale probability using at least one of the market price, the lowest desired bid price, and the purchase probability, and the number of bids that determine the number of bids depending on whether a predetermined threshold is exceeded And a determination unit.

  The purchase probability calculation unit may calculate the purchase probability by substituting a value obtained using the lowest desired bid price and the bid price into a cumulative distribution function of a normal distribution.

  The purchase probability calculation unit substitutes a composite score obtained by combining the first score based on the lowest desired bid price and the second score based on the average bid price of all bid prices into the cumulative distribution function of the normal distribution. Then, the purchase probability may be calculated.

  The first score is the value obtained by subtracting the lowest desired bid price from the bid price divided by the RMS error of all bid prices, and the second score is the RMS value obtained by subtracting the average bid price from the bid price. It may be a value divided by the error.

  The sale probability calculation unit calculates the sale probability by substituting the value obtained using the market price and the lowest desired bid price into the normal distribution cumulative distribution function when the number of bids is less than 2, and the number of bids is 2 If the number is greater than or equal to the number, the probability of sale may be calculated with the highest value among the proportion of bids exceeding the lowest desired bid price and the purchase probability in all bids.

  The server according to the present invention is a server capable of data communication via a network with a sale user terminal used by a user who sells real estate and a purchase user terminal used by a user who purchases real estate, and the sale user terminal Sent from the purchase user terminal, the market price storage unit for storing the market price according to the property information transmitted from the lowest desired bid price storage unit for storing the lowest desired bid price transmitted from the selling user terminal, A bid information storage unit for storing bid information including at least a bid price, a purchase probability calculation unit for calculating a purchase probability using the lowest desired bid price and bid price, and at least a market price, a lowest desired bid price and a purchase probability. The number of bids is determined based on the sale probability calculation unit that calculates the sale probability using one and whether a predetermined threshold is exceeded. A bid number determination unit, and having a.

  The purchase probability calculation unit may calculate the purchase probability by substituting a value obtained using the lowest desired bid price and the bid price into a cumulative distribution function of a normal distribution.

  The purchase probability calculation unit substitutes a composite score obtained by combining the first score based on the lowest desired bid price and the second score based on the average bid price of all bid prices into the cumulative distribution function of the normal distribution. Then, the purchase probability may be calculated.

  The first score is the value obtained by subtracting the lowest desired bid price from the bid price divided by the RMS error of all bid prices, and the second score is the RMS value obtained by subtracting the average bid price from the bid price. It may be a value divided by the error.

  The sale probability calculation unit calculates the sale probability by substituting the value obtained using the market price and the lowest desired bid price into the normal distribution cumulative distribution function when the number of bids is less than 2, and the number of bids is 2 If the number is greater than or equal to the number, the probability of sale may be calculated with the highest value among the proportion of bids exceeding the lowest desired bid price and the purchase probability in all bids.

  A program according to the present invention causes a computer to function as any one of the servers described above.

  A recording medium according to the present invention is a computer-readable recording medium on which the above program is recorded.

  ADVANTAGE OF THE INVENTION According to this invention, the real estate transaction system, server, program, and recording medium which calculate the transaction establishment probability with correlation with respect to both the seller side and the buyer side can be provided.

1 is a diagram illustrating an overall configuration of a real estate transaction system 100. FIG. 2 is a diagram illustrating a configuration of a server 101. FIG. It is the figure which showed the structure of the sale user terminal. 5 is a diagram showing a configuration of a purchase user terminal 103. FIG. 5 is a flowchart showing information processing between a selling user terminal 102 and a server 101. 3 is a flowchart showing information processing of a server 101. 5 is a flowchart showing information processing between the selling user terminal 102 and the server 101 and information processing between the purchasing user terminal 103 and the server 101. 5 is a flowchart showing information processing between a selling user terminal 102 and a server 101. It is the figure which showed an example of the data structure of the lowest successful bid desired price storage part. It is the figure which showed an example of the data structure of the bid information storage part 129. It is the figure which showed an example of the data structure of the market price storage part 131. FIG. It is the figure which showed an example of the data structure of the sale probability and purchase probability storage part. It is the figure which showed an example of the data structure of the parameter storage part. It is the figure which showed an example of the data structure of the user information storage part 127. FIG. It is the figure which showed an example of the property information registration screen 380. FIG. It is the figure which showed an example of the bid screen. It is the figure which showed an example of the property information management screen. It is the figure which showed an example of the bid information management screen.

  Hereinafter, an embodiment of a real estate transaction system according to the present invention will be described in detail.

  FIG. 1 is a diagram showing an overall configuration of a real estate transaction system 100 according to the present embodiment. As illustrated, the real estate transaction system 100 includes a server 101, a sale user terminal 102, and a purchase user terminal 103, and the sale user terminal 102 and the purchase user terminal 103 are connected via the network 104 to the server 101. And data communication.

  The server 101 is a computer that performs data communication with the selling user terminal 102 and the purchasing user terminal 103 and executes auction processing.

  The sale user terminal 102 is a terminal used by a user who sells real estate. Specifically, a personal computer, a mobile phone, a PDA, a smartphone, or the like can be used, and is not particularly limited. In the present invention, the number of sold user terminals 102 is not particularly limited.

  The purchase user terminal 103 is a terminal used by a user who purchases real estate. Specifically, a personal computer, a mobile phone, a PDA, a smartphone, or the like can be used, and is not particularly limited. In the present invention, the number of sold user terminals 103 is not particularly limited.

  Next, the configuration of the server 101 will be described with reference to FIG.

  FIG. 2 is a diagram illustrating a configuration of the server 101 according to the present embodiment. As illustrated, the server 101 includes a CPU 120, a RAM 121, a communication unit 122, a program storage unit 123, and a data storage unit 126 via a bus 134.

  The CPU 120 is a central processing unit that functions as the center of the server 101. The CPU 120 extracts necessary programs and data from the program storage unit 123 and the data storage unit 126, loads them into the RAM 121, and executes the programs.

  The RAM 121 is a storage device using a semiconductor storage element or the like.

  The communication unit 122 is a communication device that transmits / receives data to / from the selling user terminal 102 and the purchasing user terminal 103 via the network 104.

  The program storage unit 123 is a storage device for storing various programs. The program storage unit 123 stores a sale probability calculation unit 124 that calculates a sale probability, a purchase probability calculation unit 125 that calculates a purchase probability, and a bid number determination unit 133 that determines the number of bids depending on whether a predetermined threshold is exceeded. The sale probability calculation unit 124, the purchase probability calculation unit 125, and the number-of-bids determination unit 133 are loaded into the RAM 121 and executed by the CPU 120, whereby the sale probability calculation process and the purchase probability calculation are realized.

  The data storage unit 126 is a storage device for storing various data. The data storage unit 126 includes a user information storage unit 127, a lowest desired bid price storage unit 128, a bid information storage unit 129, a sale probability / purchase. A probability storage unit 130, a market price storage unit 131, and a parameter storage unit 132 are stored.

  The user information storage unit 127 stores information on sold users and purchased users. FIG. 14 is a diagram illustrating an example of a data structure of the user information storage unit 127. As shown in the figure, the user information storage unit 127 includes a table 360 having storage areas 361 to 366, and stores a user ID, name, age, address, mail address, and the like assigned to each user. Note that the information stored in the user information storage unit 127 is not limited to these, and information to be stored may be added or deleted as necessary.

  The lowest successful bid desired price storage unit 128 stores the lowest successful bid desired price for each property. FIG. 9 is a diagram showing an example of the data structure of the lowest desired bid price storage unit 128. As shown in the figure, the lowest desired bid price storage unit 128 includes a table 260 having storage areas 261 and 262, and the lowest desired bid price is stored for each property.

  The bid information storage unit 129 stores the bid information transmitted from the purchase user for each property. FIG. 10 is a diagram illustrating an example of a data structure of the bid information storage unit 129. As shown in the figure, the bid information storage unit 129 includes a table 280 having storage areas 281 to 284, and stores the user ID and bid price of the purchase user who transmitted the bid information for each property. The storage area 285 stores the average bid price for each property. In FIG. 10, the number of bid information items is stored up to three. However, the number of bid information items to be stored is not limited to this, and the number of bid information items to be stored can be increased or decreased as necessary. Good.

  The sale probability / purchase probability storage unit 130 stores, for each property, a sale probability that is a seller side transaction establishment probability and a purchase probability that is a buyer side transaction establishment probability. FIG. 12 is a diagram illustrating an example of the data structure of the sale probability / purchase probability storage unit 130. As illustrated, the sale probability / purchase probability storage unit 130 includes a table 320 having storage areas 321 to 325, and the sale probability is stored for each property ID. Further, a purchase probability is stored for each bid information.

  The market price storage unit 131 stores the market price as the market price for each property. FIG. 11 is a diagram illustrating an example of a data structure of the market price storage unit 131. As illustrated, the market price storage unit 131 includes a table 300 having storage areas 301 to 302, and the market price is stored for each property ID.

  The parameter storage unit 132 stores various parameters referred to by the sale probability calculation unit 124 and the purchase probability calculation unit 125 when the sale probability calculation unit 124 and the purchase probability calculation unit 125 calculate probabilities, respectively. FIG. 13 is a diagram illustrating an example of the data structure of the parameter storage unit 132. As shown in the figure, the parameter storage unit 132 includes a table 340 having storage areas 341 to 343, and various parameters used when the sales probability calculation unit 124 and the purchase probability calculation unit 125 calculate probabilities, respectively. Stored.

  Next, the configuration of the sale user terminal 102 will be described with reference to FIG.

  FIG. 3 is a diagram illustrating a configuration of the sale user terminal 102 according to the present embodiment. As illustrated, the sale user terminal 102 includes a CPU 140, a RAM 141, a communication unit 142, a program storage unit 143, an input unit 144, a display unit 145, and a sale probability storage unit 146 via a bus 147.

  The CPU 140 is a central processing unit that functions as the center of the sale user terminal 102, takes out necessary programs and data from the program storage unit 143 and the sale probability storage unit 146, loads them into the RAM 141, and executes the programs.

  The RAM 141 is a storage device using a semiconductor storage element or the like.

  The communication unit 142 is a communication device that transmits and receives data to and from the server 101 via the network 104.

  The program storage unit 143 transmits the property information to the server 101, receives the market price transmitted from the server 101, transmits the lowest desired bid price to the server 101, and the sale probability transmitted from the server 101. , Displays the received sale probability, and stores the program that causes the sale user terminal 102 to function to store the received sale probability.

  The input unit 144 is a device that accepts an input operation by a selling user, and includes, for example, a keyboard, a camera, a mouse, a microphone, a touch panel, and the like.

  The display unit 145 is a device that displays a sale probability or the like, and includes, for example, a display using a liquid crystal display element, an organic EL, or the like.

  The sale probability storage unit 146 is a storage device for storing the sale probability transmitted from the server 101.

  Next, the configuration of the purchase user terminal 103 will be described with reference to FIG.

  FIG. 4 is a diagram illustrating a configuration of the purchase user terminal 103 according to the present embodiment. As illustrated, the purchase user terminal 103 includes a CPU 160, a RAM 161, a communication unit 162, a program storage unit 163, an input unit 164, a display unit 165, and a purchase probability storage unit 166 via a bus 167.

  The CPU 160 is a central processing unit that functions as the center of the purchase user terminal 103. The CPU 160 retrieves necessary programs and data from the program storage unit 163 and the purchase probability storage unit 166, loads them into the RAM 161, and executes the programs.

  The RAM 161 is a storage device using a semiconductor storage element or the like.

  The communication unit 162 is a communication device that transmits and receives data to and from the server 101 via the network 104.

  The program storage unit 163 transmits bid information including a bid price to the server 101, receives the purchase probability transmitted from the server 101, displays the received purchase probability, and stores the received purchase probability. This is a storage device for storing a program that causes the purchased user terminal 103 to function.

  The input unit 164 is a device that accepts an input operation by a purchase user, and includes, for example, a keyboard, a camera, a mouse, a microphone, a touch panel, and the like.

  The display unit 165 is a device that displays purchase probabilities and the like, and includes, for example, a display using a liquid crystal display element, an organic EL, or the like.

  The purchase probability storage unit 166 is a storage device for storing the purchase probability transmitted from the server 101.

  Next, referring to FIG. 5, the real estate transaction system 100 according to the present embodiment from when the property information is transmitted until the sale probability is stored in the initial stage of registering the property information of the property for sale by the selling user. Will be described.

  FIG. 5 is a flowchart showing information processing between the selling user terminal 102 and the server 101. First, when a sale user who operates the sale user terminal 102 operates the input unit 144 to input property information, the sale user terminal 102 transmits property information to the server 101 (step S180). Subsequently, the server 101 receives the property information transmitted in step S180 (step S181). The server 101 may store the property information received in step S181 in a property information storage unit (not shown) stored in the data storage unit. Subsequently, the server 101 transmits the market price corresponding to the property information received in step S181 to the sale user terminal 102 (step S182). Subsequently, the selling user terminal 102 receives the market price transmitted in step S182 (step S183). Subsequently, the sold user terminal 102 transmits the lowest desired bid price to the server 101 (step S184). Subsequently, the server 101 receives the lowest desired bid price transmitted in step S184 (step S185). Subsequently, the sale probability calculation unit 124 calculates the sale probability (step S186). Subsequently, the server 101 transmits the sale probability calculated in step S186 to the sale user terminal 102 (step S187). Subsequently, the sale user terminal 102 receives the sale probability transmitted in step S187, and stores the received sale probability in the sale probability storage unit 146 (step S188). Subsequently, the sale user terminal 102 displays the sale probability received in step S188 on the display unit 145 (step S189). Subsequent to step S187, the server 101 stores the sale probability calculated in step S186 in the sale probability / purchase probability storage unit 130 (step S190). Subsequently, the server 101 stores the lowest desired bid price received in step S185 in the lowest desired bid price storage unit 128 (step S191). Note that the order of step S187, step S190, and step S191 is not limited to this. For example, the calculated sale probability is first stored in the sale probability / purchase probability storage unit 130, and the received lowest successful bid desired price is the lowest successful bid desired price. You may transmit to the sale user terminal 102, after storing in the storage part 128. FIG. Also in the sale user terminal 102, the sale probability received in step S188 may be first displayed on the display unit 145 and then stored in the sale probability storage unit 146. Further, step S190 may be performed simultaneously with step S186, and step S191 may be performed simultaneously with step S185.

  In the initial stage of registering the property information of the property to be sold by the selling user, the selling probability cannot be calculated after reflecting the bidding status from the purchasing user. This is the same even when the number of bids from the purchase user is less than two. Accordingly, in step S186, the sales probability is calculated by a method different from the case where the number of bids is two or more.

  Hereinafter, a method for calculating the sale probability in step S186 and a method for calculating the sale probability when the number of bids from the purchase user is less than two will be described (defined as method A).

In the A method, the sales probability calculation unit 124 calculates the sales probability by substituting the market price and the lowest desired bid price into a predetermined formula, and substituting the obtained value into the cumulative distribution function of the normal distribution. Specifically, the sale probability calculation unit 124 reads the market price from the market price storage unit 131 and reads the lowest desired bid price from the lowest successful bid desired price storage unit 128. Next, the sale probability calculation unit 124 performs the following calculation using the read market price and the lowest desired bid price.
Here, the offset value in Equation 1 is a value for determining / changing the range of sale probabilities calculated by the A method, and determines the sale probability when the lowest desired bid price is the same as the market price. The sale probability calculation unit 124 refers to the parameter storage unit 132 and substitutes the value of the parameter 01 for the offset value in Equation 1.

Subsequently, the sale probability calculation unit 124 substitutes the value obtained by Equation 1 into the cumulative distribution function of the normal distribution. The cumulative distribution function of the normal distribution is defined by Equation 2.
Here, when the arithmetic mean is 0 and the standard deviation is 1, Equation 2 is a cumulative distribution function of a standard normal distribution.

  Subsequently, the sale probability calculation unit 124 multiplies 100 by a value obtained by substituting it into the cumulative distribution function of the normal distribution. The value obtained thereby becomes the sale probability [%].

  According to the A method, the selling probability can be easily calculated using the market price and the lowest desired bid price in the initial stage where it is difficult to calculate the selling probability reflecting the bid situation from the purchase user. Moreover, the range of the sale probability calculated can be appropriately adjusted only by changing the offset value in Equation 1.

For example, when the lowest desired bid price is 21 million yen for a property with a market price of 20 million yen, the calculation result of Equation 1 is as follows. Note that the offset value is 0.5, which is the value of the parameter 01 in FIG.
(2100 / 2000-1) × (−5) + 0.5 = 0.25
Subsequently, the above 0.25 is substituted into the normal distribution cumulative distribution function. Here, the normal distribution into which the value obtained by Equation 1 is substituted may follow the standard normal distribution. The spreadsheet software Excel (registered trademark) provided by Microsoft Corporation can use the NORMSDIST function as follows.
NORMSDIST (0.25) = 0.5987≈0.599
Therefore, the sale probability in this case is calculated as 59.9 [%].

  Next, the operation of the real estate transaction system 100 according to this embodiment from when the bid information is transmitted until the purchase probability and the sale probability are stored will be described. First, referring to FIG. Next, the operation of the server 101 from when the purchase probability and the sale probability are stored will be described.

  FIG. 6 is a flowchart showing the information processing of the server 101. First, the server 101 waits to receive bid information transmitted from the purchase user terminal 103 (step S200). Subsequently, the server 101 receives the bid information transmitted from the purchase user terminal 103 (step S201). Subsequently, the server 101 reads, from the bid information storage unit 129, information stored as bid information of the property related to the bid information received in step S201 (step S202). Subsequently, the bid number determination unit 133 determines whether or not the total number of bids for the property related to the bid information received in step S201 is two or more (step S203). If the total number of bids for the property related to the bid information received in step S201 is two or more, the process proceeds to step S204, and if not, the process proceeds to step S211. When it is determined that the total number of bids for the property related to the bid information received in step S201 is 2 or more, the purchase probability calculation unit 125 purchases each bid information of the property related to the bid information received in step S201. The probability is calculated (step S204). Subsequently, the server 101 transmits the purchase probability calculated in step S204 to the corresponding purchase user terminal 103 (step S205). Subsequently, the server 101 stores the purchase probability calculated in step S204 in the sale probability / purchase probability storage unit 130 (step S206). Note that step S206 may be performed simultaneously with step S204. Subsequently, the sale probability calculation unit 124 calculates the sale probability (step S207). Subsequently, the server 101 transmits the sale probability calculated in step S207 to the sale user terminal 102 (step S208). Subsequently, the server 101 stores the sale probability calculated in step S207 in the sale probability / purchase probability storage unit 130 (step S209). Note that step S209 may be performed simultaneously with step S207. Subsequently, the server 101 stores the bid information received in step S201 in the bid information storage unit 129 (step S210). Note that step S210 may be performed simultaneously with step S201. On the other hand, if it is determined that the total number of bids for the property related to the bid information received in step S201 is less than 2, the purchase probability calculation unit 125 calculates the purchase probability related to the bid information received in step S201. (Step S211). Subsequently, the server 101 transmits the sale probability calculated in step S211 to the corresponding purchase user terminal 103 (step S212). Subsequently, the server 101 stores the purchase probability calculated in step S211 in the sale probability / purchase probability storage unit 130 (step S213). Note that step S213 may be performed simultaneously with step S211. Subsequently, the server 101 proceeds to step S210 described above.

  Next, the operation of the real estate transaction system 100 according to this embodiment from when the bid information is transmitted until the purchase probability and the sale probability are stored will be described. As a premise, the purchase user terminal 103 (a) is the first to transmit bid information for the property exemplified in the following description, and the second bid information is transmitted from the purchase user terminal 103 (b). And That is, the number of bids is zero until a bid is placed from the purchase user terminal 103 (a), and the number of bids for the property illustrated in the following explanation is 2 because the bid was made from the purchase user terminal 103 (b). Suppose that

7 shows information processing between the selling user terminal 102 and the server 101, information processing between the purchasing user terminal 103 (a) and the server 101, and information between the purchasing user terminal 103 (b) and the server 101. It is the flowchart which showed information processing. First,
The purchase user terminal 103 (a) transmits bid information (a) to the server 101 (step S220). Subsequently, the server 101 receives the bid information (a) transmitted in step S220 (step S221). Here, step S221 corresponds to step S201. That is, in step S203, since the bid number determination unit 133 determines that the total number of bids is less than two, the server 101 stores the bid information (a) in the bid information storage unit 129. If it is determined in S203 that the total number of bids is less than 2, the process proceeds to step S212, but the description thereof is omitted here. Subsequently, the purchase user terminal 103 (b) transmits bid information (b) to the server 101 (step S222). Subsequently, the server 101 receives the bid information (b) transmitted in step S222 (step S223). Here, step S223 also corresponds to step S201 similarly to step S221. That is, the server 101 reads the bid information (a) from the bid information storage unit 129 in step S202, and the bid number determination unit 133 determines that the total number of bids is two or more in step S203. Subsequently, the purchase probability calculation unit 125 calculates the purchase probability (a) and the purchase probability (b) for each bid information (steps S224 and S225). Here, steps S224 and 225 correspond to step S204. The order of calculating the purchase probability (a) and the purchase probability (b) is not limited to this, and may be arbitrarily determined. Subsequently, the server 101 transmits the purchase probability (a) and the purchase probability (b) calculated in steps S224 and 225 to the purchase user terminal 103 (a) and the purchase user terminal 103 (b), respectively ( Steps S226 and 229) Here, Steps S226 and 229 correspond to Step S205. Further, the order of transmitting the purchase probability (a) and the purchase probability (b) is not limited to this, and may be arbitrarily determined. The purchase user terminal 103 (a) receives the purchase probability (a) transmitted in step S226, and stores the received purchase probability in the purchase probability storage unit 166 (step S227). Subsequently, the purchase user terminal 103 (a) displays the purchase probability (a) received in step S227 on the display unit 165 (step S228). On the other hand, the purchase user terminal 103 (b) receives the purchase probability (b) transmitted in step S229, and stores the received purchase probability in the purchase probability storage unit 166 (step S230). Subsequently, the purchase user terminal 103 (b) displays the purchase probability (b) received in step S230 on the display unit 165 (step S231). Subsequent to steps S226 and 229, the server 101 stores the purchase probabilities calculated in steps S224 and 225 in the sale probability / purchase probability storage unit 130 (step S232). Here, step S232 corresponds to step S206. Note that step S232 may be performed simultaneously with steps S224 and 225. Subsequently, the sale probability calculation unit 124 calculates the sale probability (step S233). Step S233 corresponds to step S207. Subsequently, the server 101 transmits the sale probability calculated in step S233 to the sale user terminal 102 (step S234). Subsequently, the sale user terminal 102 receives the sale probability transmitted in step S234, and stores the received sale probability in the sale probability storage unit 146 (step S235). Subsequently, the sale user terminal 102 displays the sale probability received in step S235 on the display unit 145 (step S236). Subsequent to step S234, the server 101 stores the sale probability calculated in step S233 in the sale probability / purchase probability storage unit 130 (step S237). Subsequently, in addition to the bid information (a) already stored in the bid information storage unit 129, the server 101 stores the bid information (b) received in step S223 in the bid information storage unit 129 (step S238). . The order of steps S237 and 238 is not limited to this, and may be reversed. Further, step S237 may be performed simultaneously with step S233, and step S238 may be performed simultaneously with step S223.

  The purchase probability is calculated by the purchase probability calculation unit 125 in steps S224 and S225 by substituting the bid price and the lowest desired bid price into a predetermined formula, and substituting the obtained value into the cumulative distribution function of the normal distribution. Specifically, the purchase probability calculation unit 125 reads the bid information already stored in the bid information storage unit 129 from the bid information storage unit 129 and reads the lowest desired bid price from the lowest desired bid price storage unit 128. . Next, the purchase probability calculation unit 125 performs each calculation described below using the bid information received in the step immediately before the step of calculating the read bid information, the lowest desired bid price, and the purchase probability.

First, the purchase probability calculating unit 125 calculates the average bid price by performing the following calculation using the read bid information and the bid information received in the step immediately before the step of calculating the purchase probability.

Subsequently, the purchase probability calculation unit 125 performs the following calculation to calculate an RMS (Root Mean Square) error.

Subsequently, the purchase probability calculation unit 125 performs the following calculation for each bid information to calculate a first score.
Here, the first score, which is the value obtained by Equation 5, can be treated as an index based on the lowest desired bid price, that is, an absolute index indicating the attractiveness of the bid price with respect to the lowest desired bid price. it can.

Subsequently, the purchase probability calculation unit 125 performs the following calculation for each bid information to calculate a second score.
Here, the second score, which is the value obtained by Equation 6, can be treated as an index based on the average bid price, that is, a relative index among other competing bids.

However, the purchase probability can also be calculated by substituting either the first score or the second score into the cumulative distribution function of the normal distribution. However, as described above, since the first score and the second score have different characteristics, the purchase probability is calculated by substituting the combined score obtained by combining these into the cumulative distribution function of the normal distribution. It is preferable. The purchase probability calculation unit 125 performs the following calculation for each bid information to calculate a composite score.
Here, the reflection ratio of the first score in Equation 7 defines the ratio at which the first score is reflected in the composite score. The purchase probability calculation unit 125 refers to the parameter storage unit 132 and substitutes the value of the parameter 03 into the reflection ratio of the first score in Equation 7. Similarly, the reflection ratio of the second score in Equation 7 determines the ratio at which the second score is reflected in the composite score. The purchase probability calculation unit 125 refers to the parameter storage unit 132 and substitutes the value of the parameter 04 for the reflection ratio of the second score in Equation 7. By appropriately adjusting the reflection ratio of the first score and the reflection ratio of the second score, it is possible to weight which of the first score and the second score is important in calculating the purchase probability. it can.

  Subsequently, the purchase probability calculation unit 125 substitutes the value of the composite score obtained for each bid information according to Equation 7 into the cumulative distribution function of the normal distribution for each bid information.

  Subsequently, the purchase probability calculating unit 125 multiplies 100 by a value obtained by substituting it into the cumulative distribution function of the normal distribution. The value obtained thereby becomes the purchase probability [%] for each bid information.

  For example, when an extremely high bid price is bid, the purchase probability becomes a value close to 100%. Therefore, after setting the threshold value of the composite score, it is checked whether the calculated composite score exceeds the threshold value every time the composite score is calculated by Equation 7, and when the calculated composite score exceeds the threshold value, More preferably, the composite score is replaced with a threshold value. This process can be realized by referring to the parameter 02 stored in the parameter storage unit 132 by the purchase probability calculation unit 125 every time the composite score is calculated by Equation 7.

  Next, a method when the sale probability calculation unit 1254 calculates the sale probability in step S233 will be described.

  In the initial stage of registering the article information of the property for sale by the selling user or when the number of bids from the purchasing user is less than 2, the probability of sale can be calculated after reflecting the bidding status from the purchasing user. There wasn't. On the other hand, when the number of bids from the purchase user is two or more, the sale probability can be calculated after reflecting the bid situation. Therefore, in step S233, the sales probability is calculated by a method different from the initial stage of registering the property information of the property to be sold by the selling user and the case where the number of bids from the purchasing user is less than two.

  Hereinafter, a method (defined as method B) for calculating the sale probability when the number of bids from the purchase user is two or more as in step S233 will be described. It should be noted that the number of bids used as a criterion for whether to use the A method or the B method, that is, the threshold used by the bid number discrimination unit 133 does not necessarily need to be two, and is appropriately set to three or more. Needless to say, it can be changed. The threshold used by the bid number determination unit 133 in the present embodiment is the value of the parameter 06 in FIG. 13, and when the bid number determination unit 133 determines the number of bids, the bid number determination unit 133 refers to the value of the parameter 06. To do.

In the B method, the sale probability calculation unit 124 calculates the sale probability with the highest probability among the ratios of bids exceeding the lowest desired bid price and the purchase probability calculated by the purchase probability calculation unit 125 in all the number of bids. To do. Specifically, the sale probability calculation unit 124 reads the purchase probability for each bid information from the sale probability / purchase probability storage unit 130. Further, the sale probability calculation unit 124 reads the lowest successful bid desired price from the lowest successful bid desired price storage unit 128 and reads the bid information from the bid information storage unit 129. The sale probability calculation unit 124 performs the following calculation using the read lowest bid desired price and bid information.
Here, a value obtained by multiplying the value obtained by Equation 8 by 100 is the ratio [%] of bids exceeding the lowest desired bid price.

  Subsequently, the sale probability calculation unit 124 calculates the sale probability with the highest probability among the value obtained by multiplying the value obtained by Equation 8 by 100 and the purchase probability for each bid information read from the sale probability / purchase probability storage unit 130. Determine as [%].

  For example, when all the bid prices exceed the lowest desired bid price, the value obtained by Equation 8 is 1. In this case, the value obtained by multiplying 1 by 100, that is, the value obtained by Equation 8, that is, 100 [%] is inevitably determined as the sale probability. Therefore, after setting the threshold of the ratio of bids exceeding the minimum desired bid price, check whether the calculated ratio exceeds the threshold every time the ratio of bids exceeding the minimum desired bid price is calculated by Equation 8, When the calculated ratio exceeds the threshold, it is more preferable to replace the calculated ratio with the threshold. This process can be realized by the sale probability calculation unit 124 referring to the parameter 05 stored in the parameter storage unit 132 every time the ratio of bids exceeding the lowest desired bid price is calculated by Equation 8.

  Next, the operation of the real estate transaction system 100 according to the present embodiment in the case where the lowest desired bid price is changed at an arbitrary stage after registering the property information of the property for sale by the selling user will be described.

  FIG. 8 is a flowchart showing information processing between the selling user terminal 102 and the server 101. First, when a selling user who operates the selling user terminal 102 operates the input unit 144 to input a new minimum winning bid price, the selling user terminal 102 transmits a new minimum winning bid price to the server 101 ( Step S240). Subsequently, the server 101 receives the new minimum desired bid price transmitted in step S240 (step S241). Subsequently, the server 101 reads the information stored as the bid information of the property relating to the new minimum successful bid price received in step S241 from the bid information storage unit 129 (step S242). Subsequently, the number-of-bids discriminating unit 133 discriminates whether or not the number of bids for the property relating to the new minimum successful bid price received in step S241 is two or more (step S243). If the number of bids for the property related to the new minimum desired bid price received in step S241 is two or more, the process proceeds to step S244, and if not, the process proceeds to step S253. When it is determined that the number of bids for the property related to the new minimum desired bid price received in step S241 is two or more, the purchase probability calculation unit 125 calculates the purchase probability for each bid information read in step S242. (Step S244). Subsequently, the server 101 transmits the purchase probability calculated in step S244 to the corresponding purchase user terminal 103 (step S245). Subsequently, the server 101 stores the purchase probability calculated in step S244 in the sale probability / purchase probability storage unit 130 (step S246). Note that step S246 may be performed simultaneously with step S244. Subsequently, the sale probability calculation unit 124 calculates the sale probability based on the B method (step S247). On the other hand, when it is determined that the number of bids for the property related to the new minimum successful bid price received in step S241 is less than 2, the purchase probability calculation unit 125 reads the purchase probability calculation unit 125 in step S242. The purchase probability related to the bid information is calculated (step S253). Subsequently, the server 101 transmits the purchase probability calculated in step S253 to the corresponding purchase user terminal 103 (step S254). Subsequently, the server 101 stores the purchase probability calculated in step S253 in the sale probability / purchase probability storage unit 130 (step S255). Note that step S255 may be performed simultaneously with step S253. However, if there is no bid information to be read in step S242, the server 101 omits steps S253 to 255. Subsequently, the sale probability calculation unit 124 calculates the sale probability based on the A method (step S256). Subsequently, the server 101 transmits the sale probability calculated in step S247 or 256 to the sale user terminal 102 (step S248). Subsequently, the sale user terminal 102 receives the sale probability transmitted in step S248, and stores the received sale probability in the sale probability storage unit 146 (step S249). Subsequently, the sale user terminal 102 displays the sale probability received in step S249 on the display unit 145 (step S250). Subsequent to step S248, the server 101 stores the sale probability calculated in step S247 or 256 in the sale probability / purchase probability storage unit 130 (step S251). Subsequently, the server 101 stores the lowest desired bid price received in step S241 in the lowest desired bid price storage unit 128 (step S252). The order of steps S251 and 252 is not limited to this, and may be reversed. Moreover, step S251 may be performed simultaneously with step S247 or 256, and step S253 may be performed simultaneously with step S241.

  As described above, the sale user can change the lowest desired bid price at any stage after registering the property information of the item to be exhibited, and the sale user terminal 102 can change the lowest desired bid price when the lowest desired bid price is changed. An appropriate sale probability can be acquired according to a bid situation from a purchase user. In addition, when the lowest desired bid price is changed by the selling user, the purchase user terminal 103 can automatically acquire an appropriate purchase probability according to the new lowest desired bid price.

  Next, the property information registration screen displayed on the display unit 145 of the sale user terminal 102 will be described with reference to FIG.

  FIG. 15 is a diagram illustrating an example of the property information registration screen 380 displayed on the display unit 145 of the sale user terminal 102. As shown in the figure, the property information registration screen 380 is provided with fields 381 to 385 for inputting property information. When the sale user operates the input unit 144 to input property information in the fields 381 to 385, the sale user terminal 102 transmits the property information to the server 101. The server 101 transmits the market price corresponding to the property information transmitted from the sale user terminal 102 to the sale user terminal 102. Then, the market price transmitted from the server 101 is displayed in the field 386. Subsequently, when the selling user inputs the lowest desired bid price in the field 387 based on the market price displayed in the field 386, the selling user terminal 102 transmits the lowest desired bid price to the server 101. When the server 101 receives the lowest desired bid price transmitted from the selling user terminal 102, the server 101 calculates the selling probability based on the A method, and transmits the calculated selling probability to the selling user terminal 102. Then, the sale probability transmitted from the server 101 is displayed in the field 388. When the sale user presses the registration button 389 based on the sale probability displayed in the field 388, the registration of the property information is completed. Completion of the registration of the property information may be made when the sale user terminal 102 transmits a registration request to the server 101 and the server 101 receives the transmitted registration request. Further, the minimum desired successful bid price input in the field 387 may be configured to be changed based on the sale probability displayed in the field 388.

  Next, a bid screen displayed on the display unit 165 of the purchase user terminal 103 will be described with reference to FIG.

  FIG. 16 is a diagram illustrating an example of a bid screen 400 displayed on the display unit 165 of the purchase user terminal 103. As shown in the drawing, the bid screen 400 is provided with fields 401 to 405 for displaying property information. In addition, a field 406 in which the market price is displayed is displayed. When the input unit 164 is operated by the purchase user and a bid price is input in the field 407, the purchase user terminal 103 transmits bid information including the bid price to the server 101. When the server 101 receives the bid information transmitted from the purchase user terminal, the server 101 calculates the purchase probability and transmits the calculated purchase probability to the purchase user terminal 103. Then, the purchase probability transmitted from the server 101 is displayed in the field 408. When the purchase user presses the bid button 409 based on the purchase probability displayed in the field 408, the bid is completed. Completion of a bid may be made when the purchase user terminal 103 transmits a bid request to the server 101 and the server 101 receives the transmitted bid request. Further, the bid price input in the field 407 may be changed based on the sale probability displayed in the field 408.

  Next, the property information management screen 420 displayed on the display unit 145 of the sale user terminal 102 will be described with reference to FIG.

  FIG. 17 is a diagram illustrating an example of the property information management screen displayed on the display unit 145 of the sale user terminal 102. As shown in the figure, the property information management screen 420 is provided with fields 421 and 422. In the field 421, the sale probability is displayed. When the input unit 144 is operated by the selling user and a new minimum desired bid price is input in the field 422, the sold user terminal 102 transmits the new minimum desired bid price to the server 101. When the server 101 receives the new minimum desired bid price transmitted from the selling user terminal 102, the A method or the B method depends on whether the number of bids for the property related to the new minimum desired bid price is two or more. The new sale probability is calculated based on the information, and the calculated new sale probability is transmitted to the sale user terminal 102. Then, the new sale probability transmitted from the server 101 is displayed in the field 421. When the selling user presses the change button 423 based on the selling probability displayed in the field 421, the change of the lowest desired bid price is completed. Completion of the change of the lowest desired bid price may be made when the selling user terminal 102 transmits a change request to the server 101 and the server 101 receives the transmitted change request. Further, the minimum desired successful bid price input in the field 422 may be changed based on the sale probability displayed in the field 421 until the change button 423 is pressed.

  Next, the bid information management screen 440 displayed on the display unit 165 of the purchase user terminal 103 will be described with reference to FIG.

  FIG. 18 is a diagram illustrating an example of a bid information management screen displayed on the display unit 165 of the purchase user terminal 103. As shown in the figure, fields 441 and 442 are provided in the bid information management screen 440. In the field 441, the purchase probability is displayed. When the sales user operates the input unit 164 to input a new bid price in the field 442, the purchase user terminal 103 transmits bid information including the new bid price to the server 101. Upon receiving the new bid information transmitted from the purchase user terminal 103, the server 101 calculates a new purchase probability and transmits the calculated new purchase probability to the purchase user terminal 103. Then, the new purchase probability transmitted from the server 101 is displayed in the field 441. When the purchase user presses the change button 443 based on the purchase probability displayed in the field 441, the change of the bid price is completed. Completion of the change of the bid price may be made when the purchase user terminal 103 transmits a change request to the server 101 and the server 101 receives the transmitted change request. In addition, the bid price input in the field 442 may be changed based on the sale probability displayed in the field 441 until the change button 443 is pressed.

  As described above, according to the present invention, the selling user on the seller side changes the minimum desired bid price based on the selling probability and increases the selling probability, while the purchasing user on the buyer side considers the purchasing probability. In addition, the bid price is changed to increase the purchase probability. In this way, the possibility that a transaction will be established is further increased when both the seller side and the buyer side are conscious of increasing their respective probabilities to establish the transaction. In addition, the sale probability and purchase probability fluctuate in real time, so that the minimum desired bid price and bid price converge more quickly, the time to reach both of the so-called drop points is shortened, and the transaction processing server The processing burden is also reduced. Furthermore, since the sale probability and purchase probability reflect not only the price itself but also the popularity of the property, the evaluation and value of the property in the market becomes clearer.

  Further, in real estate transactions so far, information on which buyers are considering purchasing with a certain degree of motivation has been kept secret by brokers and the like. As a result, in the real estate transaction market, so-called enclosure soil was formed. According to the present invention, the evaluation of properties in the market and the transparency of transactions are ensured, and all correct information is automatically and in real time disclosed to the seller side, thus realizing a transaction in which information cannot be concealed. it can.

  Although the description has been made centering on the embodiment relating to the real estate transaction system so far, the present invention is not limited to this embodiment, and the form and program as a program for realizing the functions of the real estate transaction system are not limited to this embodiment. It may be provided or implemented as a recorded computer-readable recording medium.

  As the recording medium, a magnetic recording device, an optical disk, a semiconductor memory, an optical card, or the like can be used. For example, as a magnetic recording device, a flexible disk and a magnetic tape are used, and as an optical disk, a DVD-RAM (Digital Versatile Disc Random Access Memory), a CD-ROM (Compact Disc Read Only Memory), a CD-R (Recordable) / RW. As (ReWritable), a semiconductor memory can be a flash memory.

  The program can be distributed by selling, transferring, or lending a portable recording medium such as a CD-ROM in which the program is recorded. Alternatively, the program may be stored in another server or the like and distributed by transferring it according to a request from the user terminal or the server via a network such as the Internet.

  Further, the present invention is not only implemented by the computer executing the read program, but an OS (Operating System) operating on the computer is part of the actual processing based on the instruction of the program. And the present invention may be implemented by the processing.

  As mentioned above, although preferred embodiment of this invention was described, it cannot be overemphasized that this invention is not limited to said embodiment, A various change is possible in the range which does not deviate from the meaning of this invention.

DESCRIPTION OF SYMBOLS 100 Real estate transaction system 101 Sale user terminal 102 Purchase user terminal 103 Server 104 Network 120 CPU
121 RAM
122 communication unit 123 program storage unit 124 sale probability calculation unit 125 purchase probability calculation unit 126 data storage unit 127 user information storage unit 128 lowest desired bid price storage unit 129 bid information storage unit 130 sale probability / purchase probability storage unit 131 market price storage Section 132 Parameter storage section 133 Number-of-bids determination section 134 Bus 140 CPU
141 RAM
142 Communication Unit 143 Program Storage Unit 144 Input Unit 145 Display Unit 146 Sale Probability Storage Unit 160 CPU
161 RAM
162 communication unit 163 program storage unit 164 input unit 165 display unit 166 purchase probability storage unit 260 table 280 table 300 table 320 table 340 table 360 table 380 property information registration screen 400 bid screen 420 property information management screen 440 bid information management screen

Claims (12)

Real estate comprising a sale user terminal used by a user who sells real estate, a purchase user terminal used by a user who purchases real estate, and a server capable of data communication via the sale user terminal and the purchase user terminal via a network A trading system,
The sold user terminal is:
A communication unit that transmits property information to the server, receives a market price transmitted from the server, transmits a lowest desired bid price to the server, and receives a sale probability transmitted from the server When,
A sale probability storage unit for storing a sale probability transmitted from the server;
Have
The purchase user terminal is:
A communication unit for transmitting bid information including at least a bid price to the server, and receiving a purchase probability transmitted from the server;
A purchase probability storage unit for storing a purchase probability transmitted from the server;
Have
The server
A market price storage unit that stores the market price according to the property information transmitted from the sale user terminal;
A minimum desired bid price storage unit that stores the lowest desired bid price transmitted from the selling user terminal;
A bid information storage unit for storing the bid information transmitted from the purchase user terminal;
A purchase probability calculating unit that calculates a purchase probability using the lowest desired bid price and the bid price;
A sale probability calculation unit for calculating a sale probability using at least one of the market price, the lowest desired bid price, and the purchase probability;
A bid number discriminating unit that discriminates the number of bids according to whether a predetermined threshold is exceeded,
The real estate transaction system characterized by having.   The real estate transaction system according to claim 1, wherein the purchase probability calculating unit calculates the purchase probability by substituting a value obtained using the lowest desired bid price and the bid price into a cumulative distribution function of a normal distribution.   The purchase probability calculating unit is configured to calculate a composite score obtained by combining a first score based on the lowest desired bid price and a second score based on an average bid price of all the bid prices. The real estate transaction system according to claim 2, wherein the purchase probability is calculated by substituting into a function.   The first score is a value obtained by subtracting the minimum desired successful bid price from the bid price divided by the RMS error of all the bid prices, and the second score is the average bid from the bid price. The real estate transaction system according to claim 3, which is a value obtained by dividing a value obtained by subtracting a price by the RMS error.   The sale probability calculation unit calculates the sale probability by substituting a value obtained using the market price and the lowest desired bid price into a cumulative distribution function of a normal distribution when the number of bids is less than two, The probability of sale according to claim 4, wherein when the number of bids is two or more, the sale probability is calculated with the highest probability among the ratios of bids exceeding the lowest desired bid price and the purchase probability in all the bids. Real estate transaction system. A server capable of data communication via a network with a sold user terminal used by a user who sells real estate and a purchased user terminal used by a user who purchases real estate,
The server
A market price storage unit that stores a market price according to the property information transmitted from the sale user terminal;
A lowest desired bid price storage unit for storing the lowest desired bid price transmitted from the selling user terminal;
A bid information storage unit for storing bid information transmitted from the purchase user terminal and including at least a bid price;
A purchase probability calculating unit that calculates a purchase probability using the lowest desired bid price and the bid price;
A sale probability calculation unit for calculating a sale probability using at least one of the market price, the lowest desired bid price, and the purchase probability;
A bid number discriminating unit that discriminates the number of bids according to whether a predetermined threshold is exceeded,
The server characterized by having.   The server according to claim 6, wherein the purchase probability calculation unit calculates the purchase probability by substituting a value obtained using the lowest desired bid price and the bid price into a cumulative distribution function of a normal distribution.   The purchase probability calculating unit is configured to calculate a composite score obtained by combining a first score based on the lowest desired bid price and a second score based on an average bid price of all the bid prices. The server according to claim 6, wherein the purchase probability is calculated by substituting into a function.   The first score is a value obtained by subtracting the minimum desired successful bid price from the bid price divided by the RMS error of all the bid prices, and the second score is the average bid from the bid price. The server according to claim 6, which is a value obtained by dividing a value obtained by subtracting a price by the RMS error.   The sale probability calculation unit calculates the sale probability by substituting a value obtained using the market price and the lowest desired bid price into a cumulative distribution function of a normal distribution when the number of bids is less than two, The probability of sale according to claim 9, wherein when the number of bids is two or more, the sale probability is calculated using the highest percentage of the bid ratio and the purchase probability exceeding the lowest desired bid price in all the bids as the sale probability. server.   The program for functioning a computer as a server as described in any one of Claims 6 thru | or 10.   The computer-readable recording medium which recorded the program of Claim 11.