Towards Knowledge Graph Based Services in Accounting Use Cases

Michael Schulze; Michelle Pelzer; Markus Schröder; Christian Jilek; Heiko Maus; Andreas Dengel

In: SemanticsP&Ds 2022 Semantics Compound Volume 2022: Joint Proceedings of the Semantics co-located events: Poster&Demo track. Joint of the Semantics co-located events: Poster & Demo track (SEMANTiCS P&Ds-2022), September 13-15, Vienna, Austria, CEUR Workshop Proceedings, CEUR-WS, 10/2022.


To assist knowledge work in accounting use cases such as bookkeeping, this poster presents a pipeline for constructing an accounting knowledge graph from heterogeneous accounting resources. To show the feasibility of the approach, we applied the pipeline in a multi-group energy provider by employing real company data. A set of prototypical knowledge services was realized with the accounting knowledge graph as the basis, for example, the suggestion of similar accounting cases to the accountant. For training decision trees to predict accounts, our results suggest that using semantically enriched data from the knowledge graph leads to better results compared to not using semantically enriched dat


Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence