ADOBE had 13 patents in big data during Q2 2024. ADOBE Inc’s patents filed in Q2 2024 focus on systems for time-series anomaly detection, automatic forecasting, and automatically generating graphic design documents. These systems utilize predictive models, machine learning algorithms, and multimodal encoders to analyze data, select appropriate models, and generate design templates based on input text and images. The patents also involve generating recommendations for digital design templates based on creative segment classification and template classifications, taking into account geo-seasonal intent data. GlobalData’s report on ADOBE gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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ADOBE had no grants in big data as a theme in Q2 2024.
Recent Patents
Application: Time-series anomaly detection (Patent ID: US20240169258A1)
The patent filed by ADOBE Inc. describes a system for time-series anomaly detection that involves receiving time-series data, computing updated estimated parameters of a predictive model, generating an uncertainty interval for future observed values, determining anomalies, and generating indications for anomalies. The method involves performing rank one updates, using Bayesian linear regression, generating uncertainty intervals with a maximum a posteriori estimate, and computing updated parameters with exponentially weighted updates that decay based on time periods.
The system and method described in the patent utilize predictive models to detect anomalies in time-series data by updating estimated parameters, generating uncertainty intervals, and identifying anomalies based on comparisons with predicted values. The system is designed to handle non-stationary time-series data, perform rank one updates based on observed values, and use exponentially weighted updates to compute parameters that vary over time. Additionally, the system can be implemented using Bayesian linear regression and approximate Gaussian processes to enhance the accuracy of anomaly detection in time-series data.
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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.
