Treffer: PyKEEN 1.0: A Python Library for Training and Evaluating Knowledge Graph Embeddings.

Title:
PyKEEN 1.0: A Python Library for Training and Evaluating Knowledge Graph Embeddings.
Authors:
Ali, Mehdi1 MEHDI.ALI@CS.UNI-BONN.DE, Berrendorf, Max2 BERRENDORF@DBS.IFI.LMU.DE, Hoyt, Charles Tapley3 CHARLES.HOYT@ENVEDATX.COM, Vermue, Laurent4 LAUVE@DTU.DK, Sharifzadeh, Sahand2 SHARIFZADEH@DBS.IFI.LMU.DE, Tresp, Volker5 SHARIFZADEH@DBS.IFI.LMU.DE, Lehmann, Jens1 ENS.LEHMANN@CS.UNI-BONN.DE
Source:
Journal of Machine Learning Research. 2021, Vol. 22, p1-6. 6p.
Database:
Business Source Premier

Weitere Informationen

Recently, knowledge graph embeddings (KGEs) have received significant attention, and several software libraries have been developed for training and evaluation. While each of them addresses specific needs, we report on a community eort to a re-design and re-implementation of PyKEEN, one of the early KGE libraries. PyKEEN 1.0 enables users to compose knowledge graph embedding models based on a wide range of interaction models, training approaches, loss functions, and permits the explicit modeling of inverse relations. It allows users to measure each component's influence individually on the model's performance. Besides, an automatic memory optimization has been realized in order to optimally exploit the provided hardware. Through the integration of Optuna, extensive hyper-parameter optimization (HPO) functionalities are provided. [ABSTRACT FROM AUTHOR]

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