SAP had two patents in metaverse during Q4 2023. SAP SE has filed patents for systems and methods to generate synthetic training data sets from unstructured electronic documents for training deep learning models. The patents also cover methods for validating procurement transactions in a computer simulated environment based on applicable procurement policies. GlobalData’s report on SAP gives a 360-degreee view of the company including its patenting strategy. Buy the report here.

SAP grant share with metaverse as a theme is 0% in Q4 2023. Grant share is based on the ratio of number of grants to total number of patents.

Recent Patents

Application: Augmenting electronic documents to generate synthetic training data sets (Patent ID: US20230334309A1)

The patent filed by SAP SE describes systems, methods, and computer-readable media for generating a synthetic training data set from an original unstructured electronic document to train a deep learning model for data extraction. The process involves applying macro augmentation operations to create sub-templates representing distinct page layouts, then generating a synthetic training data set by applying geometric and semantic data augmentations to these sub-templates and the original document. This synthetic data set is then used to train the deep learning model.

The patent includes claims for computer-readable media storing instructions to perform the method, involving receiving the original electronic document with annotated data fields, generating sub-templates with distinct layouts, applying data augmentations to create synthetic electronic documents, and providing them to the deep learning model for training. The data augmentations can include shifts, clones, swaps, deletes, or crops, and users can provide rules for applying these augmentations. Additionally, the method involves identifying sections like headers, tables, and footers in the original document to guide the selection of data augmentations. Users can also specify bounding boxes for applying augmentations, and the system allows for the creation of new labels and remapping for further data augmentation.

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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.