User Tools

Site Tools


publications

Differences

This shows you the differences between two versions of the page.

Link to this comparison view

Both sides previous revision Previous revision
Next revision
Previous revision
publications [2022/02/16 17:08]
dargmints [Publications]
publications [2022/08/29 18:49] (current)
dargmints [Publications]
Line 2: Line 2:
 **Discourse Analysis and Argumentation Mining from Text Sources**\\ **Discourse Analysis and Argumentation Mining from Text Sources**\\
 **POCI-01-0145-FEDER-031460** **POCI-01-0145-FEDER-031460**
 +
 ==== Publications ==== ==== Publications ====
  
-Pedro Azevedo, Gil Rocha, Diego Esteves, Henrique Lopes Cardoso (2021). “Towards Better Evidence Extraction Methods for Fact-Checking Systems”, in 2021 IEEE/​WIC/​ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT’21), ​online, December 14-17, 2021.+Gil Rocha, Luís Trigo, Henrique Lopes Cardoso, Rui Sousa-Silva,​ Paula Carvalho, Bruno Martins, Miguel Won (2022). “[[http://​www.lrec-conf.org/​proceedings/​lrec2022/​pdf/​2022.lrec-1.201.pdf|Annotating Arguments in a Corpus of Opinion Articles]]”,​ in LREC 2022 – The 13th Language Resources and Evaluation Conference, Marseille, June 20-25, 2022, European Language Resources Association (ELRA). ISBN: 979-10-95546-72-6,​ pp. 1890-1899. 
 + 
 +Gil Rocha, Bernardo Leite, Luís Trigo, Henrique Lopes Cardoso, Rui Sousa-Silva,​ Paula Carvalho, Bruno Martins, Miguel Won (2022). “[[https://​link.springer.com/​chapter/​10.1007/​978-3-031-08473-7_21|Predicting argument density from multiple annotations]]”,​ in Rosso, P., Basile, V., Martínez, R., Métais, E., Meziane, F. (eds), 27th International Conference on Natural Language & Information Systems (NLDB 2022), Valencia, Spain, June 15-17, 2022, Springer, LNCS 13286, pp. 227-239. DOI: 10.1007/​978-3-031-08473-7_21. 
 + 
 +Gil Rocha, Henrique Lopes Cardoso (2022). “[[https://​dl.acm.org/​doi/​abs/​10.1145/​3477314.3507246|Context Matters! Identifying Argumentative Relations in Essays]]”,​ in SAC 2022 – The 37th ACM/SIGAPP Symposium On Applied Computing, virtual conference, April 25-29, 2022. 
 + 
 +Pedro Azevedo, Gil Rocha, Diego Esteves, Henrique Lopes Cardoso (2021). “[[https://​dl.acm.org/​doi/​abs/​10.1145/​3486622.3493930|Towards Better Evidence Extraction Methods for Fact-Checking Systems]]”, in 2021 IEEE/​WIC/​ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT’21), ​Association for Computing Machinery, New York, pp. 277-284, December 14-17, 2021. DOI: 10.1145/​3486622.3493930. 
 + 
 +Gil Rocha, Henrique Lopes Cardoso (2021). “[[https://​www.esann.org/​sites/​default/​files/​proceedings/​2021/​ES2021-134.pdf|Towards Robust Auxiliary Tasks for Language Adaptation]]”,​ in 29th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2021), 6-8 October 2021, online, ISBN 978287587082-7,​ pp. 269-274.
  
-Gil Rocha, Henrique Lopes Cardoso (2021). “[[https://​www.esann.org/​sites/​default/​files/​proceedings/​2021/​ES2021-134.pdf|Towards Robust Auxiliary Tasks for Language Adaptation]]”, ​in 29th European Symposium on Artificial Neural Networks, Computational Intelligence ​and Machine Learning ​(ESANN 2021), 6-8 October 2021, online, October 6-8, 2021.+Gil Rocha, Luís Trigo, Henrique Lopes Cardoso, Rui Sousa-Silva,​ Paula Carvalho, Bruno Martins ​(2021): ​Annotating Arguments ​in Opinion Articles: Analysis ​and Evaluation of the DARGMINTS Corpus ​(Technical Report).
  
 Gil Rocha, Henrique Lopes Cardoso (2021). “[[https://​link.springer.com/​chapter/​10.1007/​978-3-030-86383-8_47|Improving Transfer Learning in Unsupervised Language Adaptation]]”,​ in Farkaš, I., Masulli, P., Otte, S., Wermter, S. (Eds.), 30th International Conference on Artificial Neural Networks (ICANN 2021), Bratislava, Slovakia, September 14–17, 2021, Proceedings,​ Part V. Springer LNCS 12895, pp. 588-599. DOI: 10.1007/​978-3-030-86383-8_47. Gil Rocha, Henrique Lopes Cardoso (2021). “[[https://​link.springer.com/​chapter/​10.1007/​978-3-030-86383-8_47|Improving Transfer Learning in Unsupervised Language Adaptation]]”,​ in Farkaš, I., Masulli, P., Otte, S., Wermter, S. (Eds.), 30th International Conference on Artificial Neural Networks (ICANN 2021), Bratislava, Slovakia, September 14–17, 2021, Proceedings,​ Part V. Springer LNCS 12895, pp. 588-599. DOI: 10.1007/​978-3-030-86383-8_47.
publications.1645027723.txt.gz · Last modified: 2022/02/16 17:08 by dargmints