Présentation du premier Atelier sur l ’ Extraction et la Modélisation de Connaissances à partir de Textes Scientifiques ( Emc-Sci 2017 )
@inproceedings{Buscaldi2017PrsentationDP, title={Pr{\'e}sentation du premier Atelier sur l ’ Extraction et la Mod{\'e}lisation de Connaissances {\`a} partir de Textes Scientifiques ( Emc-Sci 2017 )}, author={D. Buscaldi and V. Presutti}, year={2017} }
The number of papers and the available scientific knowledge is growing rapidly, making increasingly harder to keep track of all the relevant knowledge that could facilitate a research endeavour. The availability of research materials on the Web and the presence of systems for exploring the research environment alleviate this issue only to some degree. I suggest that we need to switch to a modern research paradigm in which researchers will be assisted by software capable of applying data-driven… CONTINUE READING
Figures and Tables from this paper
References
SHOWING 1-10 OF 30 REFERENCES
SemEval 2017 Task 10: ScienceIE - Extracting Keyphrases and Relations from Scientific Publications
- Computer Science, Mathematics
- SemEval@ACL
- 2017
- 150
- Highly Influential
- PDF
Large-Scale Learning of Relation-Extraction Rules with Distant Supervision from the Web
- Computer Science
- International Semantic Web Conference
- 2012
- 81
- PDF
Relation Extraction: Perspective from Convolutional Neural Networks
- Computer Science
- VS@HLT-NAACL
- 2015
- 321
- PDF
ABNER: an open source tool for automatically tagging genes, proteins and other entity names in text
- Computer Science
- 2005
- 265
- PDF
Re-examining Automatic Keyphrase Extraction Approaches in Scientific Articles
- Engineering, Computer Science
- MWE@IJCNLP
- 2009
- 80
- PDF
Accurate Keyphrase Extraction from Scientific Papers by Mining Linguistic Information
- Computer Science
- CLBib@ISSI
- 2015
- 11
- PDF
Automatic Keyword Extraction from Documents Using Conditional Random Fields
- Computer Science
- 2008
- 218
- PDF
Unsupervised Relation Extraction by Massive Clustering
- Computer Science
- 2009 Ninth IEEE International Conference on Data Mining
- 2009
- 24
- PDF