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Causal graph extraction from news: a comparative study of time-series causality learning techniques
Causal graph extraction from news has the potential to aid in the understanding of complex scenarios. In particular, it can help explain and predict events, as well as conjecture about possible cause-effect connections. However, limited work has addressed the problem of large-scale extraction of cau...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
PeerJ Inc.
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9374167/ https://www.ncbi.nlm.nih.gov/pubmed/35967930 http://dx.doi.org/10.7717/peerj-cs.1066 |