Nasdaq has been granted a patent for a computer system utilizing machine learning models to predict, prioritize, and monitor data objects for improved performance. The system receives input data, predicts selection scores, determines permitted data objects, and adjusts models based on performance metrics. GlobalData’s report on Nasdaq 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 Nasdaq, AI for workflow management was a key innovation area identified from patents. Nasdaq's grant share as of February 2024 was 50%. Grant share is based on the ratio of number of grants to total number of patents.
Machine learning system for data object selection and prioritization
A recently granted patent (Publication Number: US11922217B2) discloses a computer system designed to efficiently manage and process different types of input data from multiple source nodes over a data communications network. The system includes a processing system with predictive, control, and decision-making machine learning models to predict selection scores for data objects, determine the number of permitted data objects, prioritize them based on specific criteria, monitor selected data objects, calculate performance metrics, and adjust the machine learning models for improved performance. The system iterates through these processes to enhance its overall performance, allocate resources, preprocess input data, and cluster data sets for more effective analysis.
Furthermore, the patent also covers a method and a computer-readable medium encoded with instructions that enable a computer system to execute similar operations as the described computer system. This includes defining data categories, predicting selection scores, determining permitted data objects, prioritizing them, monitoring activities, calculating performance metrics, and adjusting machine learning models for better performance. The method involves iterating through these steps, allocating resources, preprocessing input data, clustering data sets, training predictive models, setting thresholds for permitted data objects, and prioritizing data objects using heuristic mapping. The computer-readable medium allows the system to receive input data, perform the described operations, and improve the performance of the machine learning models based on the calculated performance metrics. Overall, the patent showcases a comprehensive system and method for efficient data processing and management using 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.
