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HealthECCO abstracts cluster analysis

The workflow shows how HealthECCO knowledge graph can be analyzed with different clustering methods.
Full article is available here:
https://medium.com/@artem_ryasik/extracting-insights-from-healthecco-knowledge-graph-4bbce3ade2ff

Results and analysis Extracting data Optimizing DBSCAN parameters Full article is available here:https://medium.com/@artem_ryasik/extracting-insights-from-healthecco-knowledge-graph-4bbce3ade2ff List existing memory graphNode 21030Create memory for mutual mentionsLouvainRemove existing memory graph(optional)EmbeddingsUnwind embeddings32 to 3Color by typeLouvainEuclideanPageRankBetweennesscentralityEigenVectorcentralityDegreecentralityAggregate byDBSCAN clustersOptimize DBSCANparametersAssign currentparameters valuesAssign currentparameters valuesNode 211460.6/9Get only manuallyselected nodesAggregate by LouvainPut valuesas RowIDsPick number of clouldsyou have selectedColor bymanually picked clusterPlot coloredmanually selectedclustersRename manuallyselected groupsExtracted dataused in articleManual pickingof cloudsNode 21231Manually selected nodesused in articleRename clustersNeo4j Reader Neo4j Connection Neo4j Writer Neo4j Reader Neo4j Reader Neo4j Reader Split CollectionColumn t-SNE (L. Jonsson) Color Manager Joiner Number To String Numeric Distances Domain Calculator Joiner Joiner Joiner Neo4j Reader Neo4j Reader Neo4j Reader Neo4j Reader Joiner Top K by graphmetrics DBSCAN Domain Calculator GroupBy Parameter OptimizationLoop Start ConstantValue Column ConstantValue Column Loop End DBSCAN Ungroup Column Rename Row Filter GroupBy SilhouetteCoefficient RowID k-Means Color Manager 3D ScatterPlot (Plotly) Column Rename Table Reader Cluster selectionwith scatter plots CASE Switch Start CASE Switch End Table Reader Select dataset source DBSCAN clusteranalysis CASE Switch Start CASE Switch End String Manipulation Visualize differentclusters Results and analysis Extracting data Optimizing DBSCAN parameters Full article is available here:https://medium.com/@artem_ryasik/extracting-insights-from-healthecco-knowledge-graph-4bbce3ade2ff List existing memory graphNode 21030Create memory for mutual mentionsLouvainRemove existing memory graph(optional)EmbeddingsUnwind embeddings32 to 3Color by typeLouvainEuclideanPageRankBetweennesscentralityEigenVectorcentralityDegreecentralityAggregate byDBSCAN clustersOptimize DBSCANparametersAssign currentparameters valuesAssign currentparameters valuesNode 211460.6/9Get only manuallyselected nodesAggregate by LouvainPut valuesas RowIDsPick number of clouldsyou have selectedColor bymanually picked clusterPlot coloredmanually selectedclustersRename manuallyselected groupsExtracted dataused in articleManual pickingof cloudsNode 21231Manually selected nodesused in articleRename clustersNeo4j Reader Neo4j Connection Neo4j Writer Neo4j Reader Neo4j Reader Neo4j Reader Split CollectionColumn t-SNE (L. Jonsson) Color Manager Joiner Number To String Numeric Distances Domain Calculator Joiner Joiner Joiner Neo4j Reader Neo4j Reader Neo4j Reader Neo4j Reader Joiner Top K by graphmetrics DBSCAN Domain Calculator GroupBy Parameter OptimizationLoop Start ConstantValue Column ConstantValue Column Loop End DBSCAN Ungroup Column Rename Row Filter GroupBy SilhouetteCoefficient RowID k-Means Color Manager 3D ScatterPlot (Plotly) Column Rename Table Reader Cluster selectionwith scatter plots CASE Switch Start CASE Switch End Table Reader Select dataset source DBSCAN clusteranalysis CASE Switch Start CASE Switch End String Manipulation Visualize differentclusters

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To use this workflow in KNIME, download it from the below URL and open it in KNIME:

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Created by: artem
Created at: 2022-02-03
On NodePit since: 2022-12-11
Last update: 2024-04-18
Created with KNIME version: v4.6.4
Tags: GraphNeo4jClusteringHealthECCOCovid

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