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arXiv · 1807.11761

A First Experiment on Including Text Literals in KGloVe

Michael Cochez·Martina Garofalo·Jérôme Lenßen·Maria Angela Pellegrino
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Abstract

Graph embedding models produce embedding vectors for entities and relations in Knowledge Graphs, often without taking literal properties into account. We show an initial idea based on the combination of global graph structure with additional information provided by textual information in properties. Our initial experiment shows that this approach might be useful, but does not clearly outperform earlier approaches when evaluated on machine learning tasks.

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Michael Cochez, Martina Garofalo, Jérôme Lenßen, Maria Angela Pellegrino. 2018-07-31. A First Experiment on Including Text Literals in KGloVe. https://arxiv.org/abs/1807.11761

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