The GraphRAG Manifesto: Unlock Better GenAI Results With Knowledge Graphs | Read Now

Neo4j logo

Nodes2024

Dev Conference by Neo4j

Register for NODES 24

You only need to register once to attend all sessions.

A Graph Entity Resolution Playbook

Session Track: Applications

Session Time:

Session description

Entity resolution, the process of determining which digital descriptions correspond to the same real-world entities, is an important graph use case. It is also a crucial precursor to many graph data science projects. In this session, you will learn steps that the Neo4j professional services team has used in many entity resolution projects. The steps include designing a graph data model that highlights shared identifiers, standardizing the format of node properties, identifying outlier nodes that should be excluded from the matching process, using graph data science algorithms to identify duplicate entities, using string similarity to identify misspellings, and capturing the results of entity resolution in your graph.

Speaker

photo of Nathan Smith

Nathan Smith

Senior Data Scientist, Neo4j

Nathan Smith is a Senior Data Scientist in Neo4j Professional Services. He helps customers across a range of industries get more value from their data through graph-powered machine learning. He lives in Kansas City, Missouri and is an organizer of the Data Science Kansas City Meetup.