Flipkart Internet has been granted a patent for a system and method that automatically identifies anomalous patterns in data streams. The method involves determining monitoring metrics for dimensions, comparing them at different time periods, and automatically flagging outliers as anomalies. GlobalData’s report on Flipkart Internet 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 Flipkart Internet, was a key innovation area identified from patents. Flipkart Internet's grant share as of February 2024 was 63%. Grant share is based on the ratio of number of grants to total number of patents.

Automatic identification of anomalous patterns in data streams

Source: United States Patent and Trademark Office (USPTO). Credit: Flipkart Internet Pvt Ltd

A recently granted patent (Publication Number: US11907094B2) outlines a method and system for automatically identifying anomalous patterns in data streams. The method involves receiving a stream of data, determining monitoring metrics for various dimensions at a target time, comparing these metrics with benchmark values, and identifying outliers based on predefined threshold values. The anomalous patterns are then automatically identified based on these identified outliers. The system includes an input unit, processing unit, and identification unit to carry out these functions efficiently.

Furthermore, the patent details additional features such as determining datasets based on cohorts, defining monitoring metrics based on these datasets, and iteratively comparing metrics at different time periods to establish ratios for anomaly detection. The system also allows for the comparison of multiple ratios to enhance the accuracy of identifying anomalous patterns. By incorporating these advanced functionalities, the method and system described in the patent offer a comprehensive approach to anomaly detection in data streams, providing valuable insights for various applications across industries.

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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.