MINDWALC: mining interpretable, discriminative walks for classification of nodes in a knowledge graph

MINDWALC: mining interpretable, discriminative walks for classification of nodes in a knowledge graph

Abstract Background Leveraging graphs for machine learning tasks can result in more expressive power as extra information is added to the data by explicitly encoding relations between entities. Knowledge graphs are multi-relational, directed graph representations of domain knowledge. Recently, deep...

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Bibliographic Details
Main Authors: Gilles Vandewiele, Bram Steenwinckel, Filip De Turck, Femke Ongenae
Format: Article
Language:English
Published: BMC 2020-12-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Knowledge graphs
Data mining
Explainable AI
Decision tree
Random forest
Feature extraction
Online Access:https://doi.org/10.1186/s12911-020-01134-w

Internet

https://doi.org/10.1186/s12911-020-01134-w

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