Oracle‘s patent involves analytics using automatically generated labels for time series data and numerical lists. The system assigns descriptive labels to data points, identifies patterns indicative of events affecting computing resources, and triggers responsive actions. GlobalData’s report on Oracle gives a 360-degree view of the company including its patenting strategy. Buy the report here.

According to GlobalData’s company profile on Oracle, Hybrid cloud mgmt was a key innovation area identified from patents. Oracle's grant share as of January 2024 was 70%. Grant share is based on the ratio of number of grants to total number of patents.

Automatic labeling for time series data analytics

Source: United States Patent and Trademark Office (USPTO). Credit: Oracle Corp

A recently granted patent (Publication Number: US11887015B2) discloses a method for analyzing time series datasets to identify patterns indicative of events affecting computing resources. The method involves loading multiple time series datasets, assigning labels to data points based on patterns, and conducting searches for specific label patterns across datasets. By detecting occurrences of specific labels within a threshold distance from each other, the method can identify events affecting computing resources and trigger responsive actions. The patent also covers the generation of composite labels based on identified patterns to describe events more accurately.

Furthermore, the patent includes provisions for executing queries periodically on new data to monitor events, comparing labels to baselines, and learning from user-provided labels to refine the pattern identification process. The method can also search historical data for previous occurrences of events and adjust the time window for analysis based on user requests. The patent extends to non-transitory computer-readable media storing instructions for implementing the method and a system comprising hardware processors and computer-readable media to perform the operations outlined in the patent claims. Overall, the patented method offers a systematic approach to analyzing time series data for event detection and triggering appropriate responses based on identified patterns of labels within the datasets.

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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.