Knowledge graph embedding for ecotoxicological effect prediction
Journal article, Peer reviewed
Published version
Permanent lenke
http://hdl.handle.net/11250/2637838Utgivelsesdato
2019Metadata
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- Publikasjoner fra Cristin - NIVA [2149]
- Scientific publications [1172]
Originalversjon
CEUR Workshop Proceedings. 2019, 2456, 37-40.Sammendrag
Exploring the effects of a chemical compound on a species takes a considerable experimental effort. Appropriate methods for estimating and suggesting new effects can dramatically reduce the work needed to be done by a laboratory. Here, we explore the suitability of using a knowledge graph embedding approach for ecotoxicological effect prediction. A knowledge graph has been constructed from publicly available data sets, including a species taxonomy and chemical knowledge. These knowledge sources are integrated by ontology alignment techniques. Our experimental results show that the knowledge graph and its embeddings augment the baseline models.