CoreLogic‘s patented method uses automated valuation models with machine learning algorithms to improve property value estimates. By combining sub-models with different approaches and weights based on accuracy, the ensemble model generates a final property value estimate tailored to specific use cases. GlobalData’s report on CoreLogic gives a 360-degree view of the company including its patenting strategy. Buy the report here.

According to GlobalData’s company profile on CoreLogic, Cloud gaming was a key innovation area identified from patents. CoreLogic's grant share as of January 2024 was 34%. Grant share is based on the ratio of number of grants to total number of patents.

Automated property valuation using ensemble models and machine learning

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

A recently granted patent (Publication Number: US11816122B1) discloses a computer-implemented method for estimating the value of a subject property using an ensemble model. The method involves obtaining input data related to the property, enriching the data, applying various sub-models to generate estimations of the property value, predicting errors for each estimation, determining a use case for the ensemble model, assigning weights to the sub-model outputs based on accuracy, and combining the outputs to produce a final estimate of the property value based on the use case. The use case can be selected by a user, and the sub-models include county-level subject-neighbors, appraisal adjustment regression, appraisal emulation, and property-level machine learning models.

Furthermore, the patent also describes a system and non-transitory computer storage media implementing the method. The system includes one or more computers and storage media storing instructions for performing the operations outlined in the method. The non-transitory computer storage media, when executed by a system of computers, enables the estimation of property value by applying sub-models, predicting errors, determining a use case for the ensemble model, assigning weights based on accuracy, and combining outputs to generate a final estimate. Additionally, the predicted errors of the sub-model outputs are determined using error models associated with the sub-models, which are monitored by a model surveillance system to track performance. This innovative approach to property valuation offers a comprehensive and accurate method for estimating property values by leveraging multiple sub-models and an ensemble model based on user-defined use cases.

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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.