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A blockchain-based housing rental system and method

A leasing system and blockchain technology, applied in buying/selling/leasing transactions, data processing applications, forecasting, etc., can solve problems such as idle listings, cheating landlords for renting time, inability to understand users signing electronic contracts, etc. benefits, the effect of solving the detention problem, and solving the user's rental problem

Active Publication Date: 2021-11-16
江苏三六五网络股份有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

When users choose a house type, in order to make the rental price cheaper, they often deceive the landlord about the time of renting the house, and then many users adjust the location of the rented house according to the distance from their work unit to the rented house. Although this move makes it easier for users to commute up and down Simple, but it makes many landlords complain;
[0003] At the same time, when selecting a house type on the app, because it is impossible to know whether the user is satisfied with the rented house type or when the user wants to wait for the house price to drop, but is picked up by other users, it is impossible to find a matching house in a short time, not only It wastes the waiting time of users and also makes some houses idle, unable to solve the idea of ​​landlords wanting to rent out the house, solve the urgent needs of some landlords, and it is impossible to know whether users are satisfied with the house they are looking at when actually viewing the house. At the same time, it is impossible to know whether the user can sign an electronic contract with the merchant

Method used

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  • A blockchain-based housing rental system and method
  • A blockchain-based housing rental system and method
  • A blockchain-based housing rental system and method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0068] Example 1: In the two-dimensional model, the coordinates of the user's work place are displayed as G(x,y): (550,820), and the set of coordinates of the rented houses is F{(c 1 , d 1 ),(c 2 , d 2 )...(c m , d m )}: F{(100,630),(950,850),(500,450)}, the coordinates of the house you are looking at now is Z=(a 1 ,b 1 ): Z=(350,220), the collection of time rented by different houses is T={3 months, 5 months, 7 months};

[0069] According to the formula:

[0070] In the above formula, there is an independent variable M and a dependent variable T, and the relational expression of the function is T=am i +b;

[0071]

[0072]

[0073]

[0074] P=∑(f(m i )-t i ) 2 =∑(am i +b-t i ) 2 ;

[0075]

[0076]

[0077] Thereby draw: a=0.01, b=0.83;

[0078] T=0.01m i +0.83

[0079] When M=1000, T=11;

[0080] According to the calculation, when the rented house is 1000 away from the work place, the time of the rented house is November

[0081] Through th...

Embodiment 2

[0083] Example 2: Assume that different tenants are interested in the room type of the house they actually see and the ratings of other tenants for this room type, so the tenant will select other tenants with higher similarity from the ratings generated by the same room type. Square, the set of room-mate scoring scores is H={11,2.5,8.2,7.5,4.5,9,15,16.8,12}, L 1 The set of ratings of the lessee on the house type is [8.2, 7.5, 16, 12, 15], L 2 The set of ratings of the lessee on the house type is [11, 15, 8.2, 7.5, 9], L 3 The collection of scores of the lessee on the type of room he saw is [4.5, 7.5, 16, 12, 8.2]

[0084] According to the formula:

[0085]

[0086]

[0087]

[0088] According to the results of the data, it was found that L 1 Lessee and L 3 The similarity between the tenants is the highest, so it can be submitted to L 1 The lessee recommends L 3 The house type that the lessee sees enables the lessee to find the house type that matches them faster...

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Abstract

The invention discloses a block chain-based house leasing system and method, and relates to the technical field of house leasing. The house leasing system includes a user label determination module, a lessor management module, a lessee recommendation module, and an actual house source confirmation module. The lessor management module is used to predict the user’s rental time based on the user’s previous rental information, and to give priority to recommending houses within the remaining rental time according to the fact that the first tenant clearly does not renew the lease. The lessee needs to recommend a house, and the actual room source confirmation module is used to judge whether the lessee is satisfied with the house type according to the facial expression of the user when the lessee actually visits the house. The module can recommend other tenants with the same room type and the highest similarity rate to the tenant, so that the tenant can learn more room types from other tenants.

Description

technical field [0001] The present invention relates to the technical field of house leasing, in particular to a block chain-based house leasing system and method. Background technique [0002] With the development of cities, more and more people choose to work and settle in big cities. Before buying a house in a big city, some users will choose a house on the rental app to prepare for buying a house and raising funds. Therefore, the market for house rental The vacancies are getting bigger and bigger. When users choose a house type, in order to make the rental price cheaper, they often deceive the landlord about the time of renting the house, and then many users adjust the location of the rented house according to the distance from their work unit to the rented house. Although this move makes it easier for users to commute up and down Simple, but it makes many landlords complain; [0003] At the same time, when selecting a house type on the app, because it is impossible to...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/04G06Q30/06G06Q50/16
CPCG06Q10/04G06Q30/0631G06Q30/0645G06Q50/16
Inventor 不公告发明人
Owner 江苏三六五网络股份有限公司
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