Combining Knowledge Graphs and Retrieval Augmented Generation for Enterprise Resource Planning

Combining Knowledge Graphs and Retrieval Augmented Generation for Enterprise Resource Planning

연구 분야: Databases

학회: European Conference on Information Retrieval

Generative AI applications for Enterprise Resource Planning (ERP) need to bridge structured and unstructured content. Knowledge graphs (KGs) are known to represent both unstructured and structured data. They have been proven useful for improving results beyond baseline retrieval augmented generation (RAG). In this talk we show how we utilize Generative AI and Knowledge graphs for our use cases and also present our insights on Knowledge Graph Retrieval Augmented Generation (KG-RAG).