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House resource pricing method and system

A house source and pricing technology, applied in the information field, can solve problems such as inaccurate manual pricing, achieve high pricing efficiency, realize dynamic changes, and reduce labor costs

Inactive Publication Date: 2020-05-01
青梧桐有限责任公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The present invention discloses a house source pricing method, which is used to solve the problem of inaccurate manual pricing. The method includes steps:

Method used

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  • House resource pricing method and system

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Embodiment 1

[0036] See figure 1 Shown here is an embodiment of the housing pricing method described in this application, and the method includes the following steps:

[0037] Step 101: Set up a first database. The first database stores the information data of the house to be priced; the information data of the house to be priced includes the internal information data of the house and the external information data of the house. The internal information data of the house includes the available area, orientation, And the number of rooms; the external information data of the house includes transportation facilities, whether there are elevators, and community facilities;

[0038] Step 102: Set up a second database. The second database stores market housing information data and market housing prices corresponding to the market housing information data; the market housing information data includes housing internal information data and housing external information data The internal information data of...

Embodiment 2

[0045] See figure 2 Shown is a specific embodiment of the housing pricing system described in this application. The system includes: a first database 101, a second database 102, a data acquisition module 103, a data processing module 104, a data analysis module 105, and a model training module 106 ,among them,

[0046] The first database 101 is coupled to the data acquisition module 103, and is used to store the housing information data to be priced, and provide the housing information data to be priced to the data acquisition module 103; the first database 101 is MySQL, namely a relational database management system The information data of the house to be priced includes the internal information data of the house and the external information data of the house. The internal information data of the house includes the available area, orientation, and number of rooms; the external information data of the house includes transportation facilities, whether there are elevators, and Co...

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Abstract

The invention discloses a house resource pricing method and system. The method comprises the steps of extracting first to-be-priced shell resource information data and second to-be-priced shell resource information data from a first database, searching a market shell resource price in a second database, and estimating an estimated to-be-priced shell resource price corresponding to the first to-be-priced shell resource information data through the market shell resource price; processing the first to-be-priced shell resource information data and the second to-be-priced shell resource informationdata to obtain first data and second data; substituting the first data and the estimated to-be-priced house resource price into a to-be-trained model, and training the to-be-trained model to obtain afirst pricing model; and substituting the second data into the first pricing model to calculate the price of the to-be-priced house resource. According to the invention, the to-be-priced shell resource price corresponding to the to-be-priced shell resource information can be calculated by substituting the processed to-be-priced shell resource information data into the first pricing model, and pricing and machine learning are combined to realize a non-artificial pricing system.

Description

Technical field [0001] The invention relates to the field of information technology, in particular to a housing pricing method and system. Background technique [0002] Currently in the field of long-term rental apartments, the price of the house after renovation is very important. The traditional pricing method is basically manual pricing. Manual pricing is less expensive when the number of houses to be priced is small, but once the number of houses to be priced comes up, the labor cost of manual pricing is extremely high at this time, and there will be problems with inaccurate pricing. And in a period of rapid business growth, meeting demand becomes particularly important. The existing technical solutions have the following problems: [0003] 1. When the number of houses to be priced is small, labor can still be satisfied. If the number of houses to be priced per day is more than 1,000, or even more, the labor cost becomes very expensive; [0004] 2. There will be some abnormalit...

Claims

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Application Information

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IPC IPC(8): G06Q30/02G06Q50/16
CPCG06Q30/0206G06Q50/165
Inventor 李昭陈浩高靖崔岩卢述奇陈呈张宵
Owner 青梧桐有限责任公司
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