Envestnet has been granted a patent for a system that utilizes context-based data-driven classification. The system identifies input for processing, obtains data from third-party sources, processes the input using a classifier, and combines the data with classifier output to determine a final classification. GlobalData’s report on Envestnet gives a 360-degree view of the company including its patenting strategy. Buy the report here.

According to GlobalData’s company profile on Envestnet, was a key innovation area identified from patents. Envestnet's grant share as of May 2024 was 20%. Grant share is based on the ratio of number of grants to total number of patents.

Context-based data-driven classification system and method

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

A recently granted patent (Publication Number: US11966421B2) discloses a computer-readable media storing instructions that, when executed by a device's processors, enable the device to identify input for processing using a classifier. The input is selected based on a prediction that it will be incorrectly classified by the classifier. The device then uses this input to gather data from third-party sources to provide context, processes the input with the classifier to generate output classifications, and combines the third-party data with the classifier's output to determine a final classification.

Furthermore, the patent details the use of machine learning models as classifiers, the prediction of incorrect classifications based on input characteristics, and the formulation of queries to third-party data sources based on the input. The device is also directed to normalize the data obtained from these sources and utilize a second machine learning classifier to process features from both the third-party data and the classifier's output to determine the final classification. This innovative approach aims to enhance classification accuracy by leveraging external data sources and advanced machine learning techniques.

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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.