Automatically determining a current value for a home

Patent metadata

Field	Value
Publication number	US-10074111-B2
Application number	US-201414167962-A
Country	US
Kind code	B2
Filing date	Jan 29, 2014
Priority date	Feb 3, 2006
Publication date	Sep 11, 2018
Grant date	Sep 11, 2018

Abstract

A facility for valuing a distinguished home located in a distinguished geographic area is described. The facility receives home attributes for the distinguished home. The facility obtains valuation for the distinguished home by applying to the received home attributes evaluation model for homes in the distinguished geographic area that has been trained using selling price and home attribute data from homes recently sold in the distinguished geographic area. The facility reports the obtained valuation for the distinguished home.

First claim

We claim:

1. A method, in a computing system having a memory and a processor, for valuing a distinguished home located in a distinguished geographic area, comprising:
retrieving, by the processor, home sales data for the distinguished geographic area from a plurality of source systems over a computer network, the home sales data comprising a plurality of entries each indicating, for a home located in the distinguished geographic area that was recently sold, a selling price, and, for each of a plurality of attributes, the value of the attribute for the home;
creating, by the processor, a plurality of classification trees for the distinguished geographic area;
storing each of the created plurality of classification trees for the distinguished area in the memory;
for each of the classification trees, by the processor:
randomly selecting a proper subset of the plurality of entries;
randomly selecting a proper subset of the plurality of attributes;
for each of the selected attributes, determining the full range of values of the selected attribute among the selected entries;
establishing a root node representing all of the selected entries and the full range of values of each of the selected attributes;
for each node of the tree:
determining the information gain borne by each possible split of each of the ranges of the selected attributes represented by the node to the selling prices of the entries represented by the node;
when the greatest information gain of a possible split exceeds the information gain of the node:
performing the possible split having the greatest information gain to divide the range into two subranges at a point in the attribute range that produces the largest variance between an average selling price for the subranges to an average selling price for the range;
for each of the two subranges, establishing a child of the node representing the subrange and the homes represented by the node whose attribute values fall into the subrange;

when the greatest information gain of a possible split does not exceed the information gain of the node, identifying the node as a leaf node and calculating a mean selling price for the homes represented by the node;

for each of a proper subset of the plurality of entries that excludes the selected entries:
identifying a leaf node of the classification tree representing attribute ranges containing the entry's attributes;
comparing the price of the identified leaf node to the selling price of the entry;

scoring the classification tree based on the extent to which the prices of the identified leaf nodes differed from the corresponding selling prices;

receiving, by the processor, attributes of the distinguished home from a user device over the computer network;
for each of the classification trees, identifying, by the processor, a leaf node of the classification tree representing attribute ranges containing the distinguished home's attributes;
determining, by the processor, an average of the price of the identified leaf node in each of the trees that is weighted by the tree's score; and
reporting the determined average as the value of the distinguished home to the user device.

2. A computer-readable medium not constituting transitory signals whose contents cause a computing system to perform a method for valuing a distinguished home located in a distinguished geographic area in cooperation with a memory, the method comprising:
receiving home attributes for the distinguished home from a client device over a computer network;
storing the received home attributes in the memory;
obtaining, with the processor, a valuation for the distinguished home by applying to the home attributes stored in the memory a weighted classification tree-based valuation model, stored in the memory, for homes in the distinguished geographic area trained using selling price and home attribute data from homes recently sold in the distinguished geographic area,
wherein the valuation model is a compound model that includes a component for all homes in the distinguished geographic area, as well as a component for the most highly-valued homes in the distinguished geographic area; and
reporting, with the processor, the obtained valuation for the distinguished home to the client device.

3. The computer-readable medium not constituting transitory signals of claim 2 wherein the received home attributes are retrieved from a database of public information.

4. The computer-readable medium not constituting transitory signals of claim 2 wherein the received home attributes are inputted by a person knowledgeable about the attributes of the distinguished home.

5. The computer-readable medium not constituting transitory signals of claim 2 wherein the compound valuation model is applied by first applying the component for all homes in the distinguished geographic area, and using the produced valuation to weight valuations generated for the home by the two components in the reported valuation.

6. The computer-readable medium not constituting transitory signals of claim 2 , further comprising:
determining that a home attribute value for the distinguished home is unavailable; and
in response to the determination, imputing a value for the attribute for the distinguished home.

7. The computer-readable medium not constituting transitory signals of claim 6 , further comprising choosing as the imputed attribute value the median value of the attribute among homes recently sold in the distinguished geographic area.

8. The computer-readable medium not constituting transitory signals of claim 6 , further comprising choosing as the imputed attribute value the mode value of the attribute among homes recently sold in the distinguished geographic area.

9. The computer-readable medium not constituting transitory signals of claim 2 , the method further comprising, before reporting the obtained valuation for the distinguished home, blending into the obtained valuation an earlier-reported valuation for the distinguished home.

10. The computer-readable medium not constituting transitory signals of claim 9 wherein the blending comprises generating a weighted average of the obtained valuation and the earlier-reported valuation in which the earlier-reported valuation is more heavily weighted than the obtained valuation.

11. The computer-readable medium not constituting transitory signals of claim 2 wherein the valuation model is comprised of a first constituent valuation model trained using selling price and home attribute data from homes recently sold in the distinguished geographic area at the highest selling prices and a second constituent valuation model trained using selling price and home attribute data from homes recently sold in the distinguished geographic area at all selling prices, and wherein obtaining a valuation for the distinguished home comprises blending the constituent valuations obtained by applying each of the constituent valuation models to the received home attributes.

12. The computer-readable medium not constituting transitory signals of claim 2 wherein the valuation model is comprised of a first constituent valuation model trained using selling price and home attribute data from homes recently sold in the distinguished geographic area at the highest selling prices and a second constituent valuation model trained using selling price and home attribute data from homes recently sold in the distinguished geographic area at all selling prices, and wherein obtaining a valuation for the distinguished home comprises:
applying the second constituent model to obtain the second constituent valuation;
if the obtained second constituent valuation is bel

Assignees

• Zillow Inc

Inventors

• Humphries Stanley B
• Xiang Dong
• Chung Kyusik
• Burstein Jonathan Lee

Classifications

• G06Q30/02

  Marketing; Price estimation or determination; Fundraising · CPC title

• G06Q50/16

  Real estate · CPC title

• G06Q30/0278 Primary

  Product appraisal · CPC title