# A First Experiment on Including Text Literals in KGloVe

arXiv: https://arxiv.org/abs/1807.11761 · HTML: https://mlsanity.com/paper/1807.11761/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 31 Jul 2018.

## Built on by (most cited first, 1 of 1)

- [End-to-End Learning on Multimodal Knowledge Graphs](https://mlsanity.com/paper/2309.01169/) (2023)

## Abstract (arXiv)

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.