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This dataset is a knowledge graph extracted from a triplestore covering information about the journal Scientometrics and modelled according to the OpenCitations Data Model. The original triplestore is available here. This KG was extracted for a research project on knowledge graph embeddings (KGEs) for author disambiguation. Structural triples of the knowledge graph are split into training, testing and validation for applying representation learning methods. Textual literals and numeric literals were stored separately in order to implement multimodal approaches for KGEs (see arXiv:1802.00934). For the same reason, textual literals and numeric literals are already stored into sentence embeddings and a numeric matrix respectively in the files textual_literals.npy and numeric_literals.npy. For the script used to gather this dataset see the GitHub repository: https://github.com/sntcristian/and-kge/tree/main/open-citations.
kg, scholarly data, knowledge graph, linked data, embeddings, scientometrics
kg, scholarly data, knowledge graph, linked data, embeddings, scientometrics
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 6 | |
| downloads | 3 |

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