SAP had 17 patents in ecommerce during Q2 2024. The patents filed by SAP SE in Q2 2024 focus on improving recommendation services in sparse data scenarios, compensating for environmental impacts in data centers, collecting user feedback efficiently, and determining customer adoption based on monitored data. These technologies utilize techniques such as cold and freezing generated item start, embeddings for distance determination, and machine learning models for generating adoption scores. Overall, these innovations aim to enhance user experience, sustainability, and decision-making processes within the digital landscape. GlobalData’s report on SAP gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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SAP had no grants in ecommerce as a theme in Q2 2024.
Recent Patents
Application: Solving sparse data problems in a recommendation system with cold start (Patent ID: US20240202797A1)
The patent filed by SAP SE introduces a method and system for recommendation services to address sparse data scenarios by utilizing a cold generated item start technique. This technique involves building a matrix representing correlations between generated items, embedding representations of these items into a vector space, and finding a warm generated item as a proxy for the cold item. The system further includes filtering mechanisms, recommendation processing based on the matrix, and communication of recommendations to users or other systems. By employing embeddings and nearest neighbor search techniques, the technology enables recommendation services to function effectively even with limited transaction data.
The patent outlines a computer-implemented method, a computing system, and computer-readable media storing instructions for implementing the recommendation system. It details the process of identifying cold and warm generated items, utilizing embeddings and matrix operations, and responding to recommendation requests. The system also incorporates category filtering, text-based representations of items in the vector space, and mechanisms for handling incoming item recommendations. Overall, the technology described in the patent aims to enhance recommendation services by overcoming sparse data challenges and providing accurate recommendations based on item correlations and embeddings in a high-dimensional vector space.
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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.
