ADOBE had 170 patents in artificial intelligence during Q1 2024. ADOBE Inc’s patents filed in Q1 2024 focus on innovative systems and methods for distributing digital content across platforms using trend-setting participants, generating causal-based models for event attribution, recognizing tables in images using machine learning models, processing queries using masked language models, and employing arrival times with confidence scores as search facets for identifying items. These patents showcase ADOBE‘s commitment to advancing technology in various domains such as digital content distribution, machine learning, and search systems. 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 grant share with artificial intelligence as a theme is 57% in Q1 2024. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Utilizing trend setter behavior to predict item demand and distribute related digital content across digital platforms (Patent ID: US20240104619A1)
The patent filed by ADOBE Inc. describes a system, method, and computer-readable media for distributing digital content across various platforms using trend-setting participants. The system generates affinity metrics for digital items based on attributes of digital posts by trend-setting participants and determines predicted demand metrics for these items on digital platforms. By using these metrics, the system distributes digital content related to the items for display on client devices via the platforms. The system also determines visual similarity between items featured in digital posts and digital items, as well as color palettes portrayed in the posts and the digital items.
Furthermore, the system determines trend-setting scores for participants on digital platforms based on their activities and identifies trend-setting participants. It then distributes digital content based on predicted demand metrics, ensuring that items with higher predicted demand are displayed more prominently. The system also considers the visual similarity between items featured in digital posts and digital items when distributing content. Additionally, the system can determine trend-setting scores for participants based on the digital items they feature on platforms, and it uses behavioral metrics to identify trend-setting participants and distribute digital content accordingly.
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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.
