Sampo Pyysalo
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Sampo Pyysalo is a person.
References
- http://dblp.uni-trier.de/pers/hd/p/Pyysalo:Sampo
- Google Scholar Author Page: https://scholar.google.com/citations?user=GUHpTS0AAAAJ
2016
- (Nivre et al., 2016) ⇒ Joakim Nivre, Marie-Catherine De Marneffe, Filip Ginter, Yoav Goldberg, Jan Hajič, Christopher D. Manning, Ryan McDonald, Slav Petrov, Sampo Pyysalo, Natalia Silveira, Reut Tsarfaty, Daniel Zeman. (2016). “Universal Dependencies V1: A Multilingual Treebank Collection.” In: Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16).
2012
- (Stenetorp et al., 2012) ⇒ Pontus Stenetorp, Sampo Pyysalo, Goran Topić, Tomoko Ohta, Sophia Ananiadou, and Jun'ichi Tsujii. (2012). “BRAT: A Web-based Tool for NLP-assisted Text Annotation.” In: Proceedings of the Demonstrations at the 13th Conference of the European Chapter of the Association for Computational Linguistics.
2011
- (Kim et al., 2011) ⇒ Jin-Dong Kim, Sampo Pyysalo, Tomoko Ohta, Robert Bossy, Ngan Nguyen, Jun’ichi Tsujii. (2011). “Overview of BioNLP Shared Task 2011.” In: Proceedings of BioNLP Shared Task 2011 Workshop (BioNLP 2011)
2008
- (Pyysalo, 2008) ⇒ Sampo Pyysalo. (2008). “A Dependency Parsing Approach to Biomedical Text Mining." PhD thesis, Turku Centre for Computer Science.
- (Airola et al., 2008) ⇒ Antti Airola, Sampo Pyysalo, Jari Björne, Tapio Pahikkala, Filip Ginter, Tapio Salakoski. (2008). “A Graph Kernel for Protein-Protein Interaction Extraction.” In: Proceedings of BioNLP 2008 (BioNLP 2008).
- (Heimonen et al., 2008) ⇒ Juho Heimonen, Sampo Pyysalo, Filip Ginter, and Tapio Salakoski. (2008). “Complex-to-Pairwise Mapping of Biological Relationships Using a Semantic Network Representation.” In: Proceedings of the Third International Symposium on Semantic Mining in Biomedicine (SMBM 2008).
- ABSTRACT: This study examines representations of protein-protein interactions focusing on the mapping between simple, pairwise annotation and complex, structured annotation. A simple semantic network representation equivalent to the BioInfer predicate formalism is introduced and used to transform the complex annotation of BioInfer into pairwise annotation through hand-written rules. Evaluation shows that this binarisation can be largely validly performed with limited loss of information, but also reveals specific challenges. The binarised BioInfer is the first corpus of this type where the inclusion rules are formalised to the level of a computational implementation and is freely available at http://www.it.utu.fi/BioInfer.
2007
- (Pyysalo et al., 2007) ⇒ Sampo Pyysalo, Filip Ginter, Juho Heimonen, Jari Bj¨orne, Jorma Boberg, Jouni J¨arvinen, and Tapio Salakoski. (2007). BioInfer: A corpus for information extraction in the biomedical domain. BMC Bioinformatics, 8(1).