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Entity resolution, also known as Data Matching or Record linkage is the task of finding a data set that refer to the same or similar real entity across different digital entities present on same or different data sets. Record linking is necessary when joining different entities which are similar and may or may not share some common identifiers. …

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neo4j-graph-examples/entity-resolution

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entity resolution icon

Entity-Resolution-Demonstration Graph Example

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

Nodes 1267 Relationships 1939

model
Figure 1. Model
example
Figure 2. Example
Example Query:
MATCH (u:User{state: $state} )-[:WATCHED]->(m)-[:HAS]->(g:Genre)RETURNg.nameasgenre,count(g)asfreqORDER BYfreqDESC

Setup

This is for Neo4j version: 4.4

Required plugins: apoc, graph-data-science

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

Load graph data via the following:

Data files:true

Import flat files (csv, json, etc) using Cypher’sLOAD CSV,APOC library, orother methods.

  • Drop the file into theFiles section of a project in Neo4j Desktop. Then choose the option toCreate 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"]

Feedback

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

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Entity resolution, also known as Data Matching or Record linkage is the task of finding a data set that refer to the same or similar real entity across different digital entities present on same or different data sets. Record linking is necessary when joining different entities which are similar and may or may not share some common identifiers. …

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