HORUS-NER: A Multimodal Named Entity Recognition Framework for Noisy Data. Esteves, D., Marcelino, J., Chawla, P., Fischer, A., & Lehmann, J. In Advances in Intelligent Data Analysis XIX - 19th International Symposium on Intelligent Data Analysis, IDA 2021, Porto, Portugal, April 26-28, 2021, Proceedings, volume 12695, of Lecture Notes in Computer Science, pages 89–100, 2021. Springer.
HORUS-NER: A Multimodal Named Entity Recognition Framework for Noisy Data [link]Paper  doi  bibtex   
@inproceedings{DBLP:conf/ida/EstevesMCF021,
  author     = {Diego Esteves and
Jos{\'e} Marcelino and
Piyush Chawla and
Asja Fischer and
Jens Lehmann},
  bibsource  = {dblp computer science bibliography, https://dblp.org},
  biburl     = {https://dblp.org/rec/conf/ida/EstevesMCF021.bib},
  booktitle  = {Advances in Intelligent Data Analysis XIX - 19th International Symposium
on Intelligent Data Analysis, IDA 2021, Porto, Portugal, April 26-28,
2021, Proceedings},
  doi        = {10.1007/978-3-030-74251-5\_8},
  keywords   = {76-8485},
  pages      = {89--100},
  publisher  = {Springer},
  series     = {Lecture Notes in Computer Science},
  timestamp  = {Thu, 14 Oct 2021 01:00:00 +0200},
  title      = {H{O}RU{S}-N{E}R: {A} Multimodal {N}amed {E}ntity {R}ecognition {F}ramework for
{N}oisy {D}ata},
  url        = {https://doi.org/10.1007/978-3-030-74251-5\_8},
  volume     = {12695},
  year       = {2021}
}

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