Intuit has been granted a patent for a computer-implemented method that detects data errors by analyzing user input against valid and invalid data sets. The system generates approximations based on kernel density estimates and uses a likelihood ratio test to classify the input as valid or invalid, triggering corrective actions if needed. GlobalData’s report on Intuit gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on Intuit, Dynamic premium pricing was a key innovation area identified from patents. Intuit's grant share as of May 2024 was 40%. Grant share is based on the ratio of number of grants to total number of patents.
Detecting data errors using likelihood ratio test statistic
A recently granted patent (Publication Number: US12001840B1) outlines a computer-implemented method for detecting data errors. The method involves receiving a new value as user input for a data field, generating histogram-based approximations of kernel density estimates based on valid and invalid data associated with the field, determining the likelihood of the new value being valid or invalid, computing a likelihood ratio test statistic, and classifying the new value as valid or invalid based on this statistic. If classified as invalid, corrective actions are taken to rectify the error.
Furthermore, the patent details the process of determining mean values for valid data, calculating log ratios, generating kernel density estimates, and applying various techniques such as simple moving averages or exponential smoothing. The method also involves computing the log ratio of the new value to the mean value associated with the data field, utilizing a Gaussian kernel function, and adjusting bin width sizes in the histogram-based approximations. The apparatus described in the patent includes a memory with computer-executable instructions and a processor to execute the method for detecting data entry errors, emphasizing the importance of classifying data accurately and taking corrective actions when errors are detected.
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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.
