Micseb / entity-resolution

Entity resolution, also known as Data Matching or Record linkage

Entity-Resolution-Demonstration Graph Example

Description: Entity Resolution, Record Linkage and Similarity wise recommendation with Neo4j

Nodes 1267 Relationships 1939

Figure 1. Model

Figure 2. Example

Example Query:

MATCH (u:User {state: $state} )-[:WATCHED]->(m)-[:HAS]->(g:Genre)

RETURN g.name as genre, count(g) as freq
ORDER BY freq DESC

Setup

This is for Neo4j version: 4.4

Required plugins: apoc, graph-data-science

Rendered guide available via: :play https://guides.neo4j.com/sandbox/entity-resolution

Unrendered guide: documentation/entity-resolution.adoc

Load graph data via the following:

Data files: true

Import flat files (csv, json, etc) using Cypher’s LOAD CSV, APOC library, or other methods.

Dump file: data/entity-resolution-44.dump

• Drop the file into the Files section of a project in Neo4j Desktop. Then choose the option to Create new DBMS from dump option from the file options.

• Use the neo4j-admin tool to load data from the command line with the command below.

bin/neo4j-admin load --from data/entity-resolution-44.dump [--database "database"]

• Upload the dump file to Neo4j Aura via https://console.neo4j.io/#import-instructions

Feedback

Feel free to submit issues or pull requests for improvement on this repository.