Zillow Group’s patent involves a system for estimating values based on specified variables. The technology uses machine learning models to ensure consistency in estimated values between different sets of variables. The patent aims to provide accurate and reliable estimates for various occurrences. GlobalData’s report on Zillow Group gives a 360-degree view of the company including its patenting strategy. Buy the report here.

According to GlobalData’s company profile on Zillow Group, 3d modelling and rendering was a key innovation area identified from patents. Zillow Group's grant share as of January 2024 was 58%. Grant share is based on the ratio of number of grants to total number of patents.

Value estimation using machine learning models with constraints

Source: United States Patent and Trademark Office (USPTO). Credit: Zillow Group Inc

A recently granted patent (Publication Number: US11886962B1) discloses a non-transitory computer-readable medium containing instructions that enable a computing system to construct a machine learning model. This model estimates a multiplier to adjust the value of a dependent variable predicted by a second machine learning model for a different set of independent variables. The patent emphasizes the use of a first machine learning model with declining complexity sub-models to meet specific constraints, ensuring the dependent variable's value does not vary in the opposite direction between different sets of independent variables.

Furthermore, the patent details the storage of a data structure defining the second machine learning model, which predicts the dependent variable for various independent variable value sets. The second machine learning model ensures consistency in predicting the dependent variable, even when the distinguished independent variable varies between sets. The patent also outlines the process of subjecting independent variable values to the first machine learning model to obtain the dependent variable's value, guaranteeing consistency when the distinguished independent variable changes direction. Additionally, the patent includes the use of constrained and unconstrained spline functions in different sub-models to enhance the accuracy of predictions and ensure the output falls within predetermined ranges for specific independent variables.

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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.