SAP had 189 patents in digitalization during Q4 2023. The patents filed by SAP SE in Q4 2023 focus on techniques for graph processing algorithms on heterogeneous graphs, determining data subsets responsive to queries using imprints, maintaining data separation during data consolidation, integrating data from different instances of a data source, and providing a scalable solution for identifying and processing large line item events efficiently. 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 digitalization as a theme is 48% in Q4 2023. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Adjacency structure for heterogeneous graph data (Patent ID: US20230418870A1)
The patent filed by SAP SE describes a method for generating an adjacency structure for a heterogeneous graph, including vertex and edge adjacency structures, to facilitate the execution of graph processing algorithms on the graph. The system involves data processors and memory storing instructions for generating the adjacency structure and executing the graph processing algorithm based on it. The system also includes vertex and edge dictionaries for unique identification and adjacency lists for specifying neighboring vertices and edges.
The system further involves operations for handling external and internal keys for identifying vertices or edges in the heterogeneous graph, ensuring correct key types and values, and retrieving internal keys based on dictionaries. Additionally, the system allows for identifying labels and internal identifiers within the adjacency structure and dictionaries, enabling the retrieval of external keys. The graph processing algorithm includes various functions like subgraph, inverse graph, shortest path, and traversal methods. Overall, the system and method aim to efficiently process and analyze heterogeneous graphs with multiple vertex and edge tables, providing a comprehensive approach to graph processing algorithms and data management.
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