Resources - Graphaware

Leveraging LLMs for Intelligence Analysis

NODES 2023 – Graph-based Entity Resolution for Intelligence Analysis

Entity Resolution (ER) draws connections between scattered, incomplete, and inconsistent records to resolve unique entities. ER is relevant in intelligence analysis, in which organized, complete, and consistent information is crucial …

NODES 2023 – Relation Extraction: Dependency Graphs vs. Large Language Models

Entity Resolution (ER) draws connections between scattered, incomplete, and inconsistent records to resolve unique entities. ER is relevant in intelligence analysis, in which organized, complete, and consistent information is crucial …

NODES2022 – Data Management with Knowledge Graphs Bringing Archives to Life

Vlasta Kůs is Lead Data Scientist at GraphAware and presented at NODES2022. Public archives contain incredible amount of knowledge. In this session, we’ll cover a real use case of building …

NODES2022 – Temporal Graph Analysis

Fabio Montagna is Lead Machine Learning Engineer at GraphAware and presented Temporal Graph Analysis at NODES2022. In this session, we’ll share our experience with horizon scanning over a graph of …

NODES2022 – Building a Neo4j/Python OGM

Estelle Scifo is a Machine Learning Engineer at GraphAware and presented at NODES2022. Leverage Cypher map projections and Python dynamic typing to build an Object Graph Mapper for Neo4j. In …