A4 Article in conference proceedings
A Configurable Evaluation Framework for Node Embedding Techniques (2019)

Pellegrino, M. A., Cochez, M., Garofalo, M., & Ristoski, P. (2019). A Configurable Evaluation Framework for Node Embedding Techniques. In P. Hitzler, S. Kirrane, O. Hartig, V. de Boer, M.-E. Vidal, M. Maleshkova, S. Schlobach, K. Hammar, N. Lasierra, S. Stadtmüller, K. Hose, & R. Verborgh (Eds.), The Semantic Web : ESWC 2019 Satellite Events, Revised Selected Papers (pp. 156-160). Springer. Lecture Notes in Computer Science, 11762. https://doi.org/10.1007/978-3-030-32327-1_31

JYU authors or editors

Publication details

All authors or editors: Pellegrino, Maria Angela; Cochez, Michael; Garofalo, Martina; Ristoski, Petar

Parent publication: The Semantic Web : ESWC 2019 Satellite Events, Revised Selected Papers

Parent publication editors: Hitzler, Pascal; Kirrane, Sabrina; Hartig, Olaf; de Boer, Victor; Vidal, Maria-Esther; Maleshkova, Maria; Schlobach, Stefan; Hammar, Karl; Lasierra, Nelia; Stadtmüller, Steffen; Hose, Katja; Verborgh, Rube


  • European Semantic Web Conference

Place and date of conference: Portorož, Slovenia,

ISBN: 978-3-030-32326-4

eISBN: 978-3-030-32327-1

Journal or series: Lecture Notes in Computer Science

ISSN: 0302-9743

eISSN: 1611-3349

Publication year: 2019

Number in series: 11762

Pages range: 156-160

Number of pages in the book: 302

Publisher: Springer

Place of Publication: Cham

Publication country: Switzerland

Publication language: English

DOI: https://doi.org/10.1007/978-3-030-32327-1_31

Publication open access: Not open

Publication channel open access:


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.

Keywords: data mining; machine learning; semantic web

Free keywords: evaluation framework; node embedding; machine learning; semantic tasks

Contributing organizations

Ministry reporting: Yes

Reporting Year: 2019

JUFO rating: 1

Last updated on 2022-24-11 at 22:23