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A Configurable Evaluation Framework for Node Embedding Techniques

: Pellegrino, M.A.; Cochez, M.; Garofalo, M.; Ristoski, P.


Hitzler, P.:
The Semantic Web: ESWC 2019 Satellite Events : ESWC 2019 Satellite Events, Portorož, Slovenia, June 2-6, 2019, Revised Selected Papers
Cham: Springer Nature, 2019 (Lecture Notes in Computer Science 11762)
ISBN: 978-3-030-32326-4 (Print)
ISBN: 978-3-030-32327-1 (Online)
Extended Semantic Web Conference (ESWC) <16, 2019, Portoroz/Slovenia>
Conference Paper
Fraunhofer FIT ()

While Knowledge Graphs (KG) are graph shaped by nature, most traditional data mining and machine learning (ML) software expect data in a vector form. Several node embedding techniques have been proposed to represent each node in the KG as a low-dimensional feature vector. A node embedding technique should preferably be task independent. Therefore, when a new method has been developed, it should be tested on the tasks it was designed for as well as on other tasks. We present the design and implementation of a ready to use evaluation framework to simplify the node embedding technique testing phase. The provided tests range from ML tasks, semantic tasks to semantic analogies.