Natural Language Processing for Intelligent Access to Scientific Information

Horacio Saggion, Francesco Ronzano


Abstract
During the last decade the amount of scientific information available on-line increased at an unprecedented rate. As a consequence, nowadays researchers are overwhelmed by an enormous and continuously growing number of articles to consider when they perform research activities like the exploration of advances in specific topics, peer reviewing, writing and evaluation of proposals. Natural Language Processing Technology represents a key enabling factor in providing scientists with intelligent patterns to access to scientific information. Extracting information from scientific papers, for example, can contribute to the development of rich scientific knowledge bases which can be leveraged to support intelligent knowledge access and question answering. Summarization techniques can reduce the size of long papers to their essential content or automatically generate state-of-the-art-reviews. Paraphrase or textual entailment techniques can contribute to the identification of relations across different scientific textual sources. This tutorial provides an overview of the most relevant tasks related to the processing of scientific documents, including but not limited to the in-depth analysis of the structure of the scientific articles, their semantic interpretation, content extraction and summarization.
Anthology ID:
C16-3003
Volume:
Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Tutorial Abstracts
Month:
December
Year:
2016
Address:
Osaka, Japan
Editors:
Marcello Federico, Akiko Aizawa
Venue:
COLING
SIG:
Publisher:
The COLING 2016 Organizing Committee
Note:
Pages:
9–13
Language:
URL:
https://aclanthology.org/C16-3003
DOI:
Bibkey:
Cite (ACL):
Horacio Saggion and Francesco Ronzano. 2016. Natural Language Processing for Intelligent Access to Scientific Information. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Tutorial Abstracts, pages 9–13, Osaka, Japan. The COLING 2016 Organizing Committee.
Cite (Informal):
Natural Language Processing for Intelligent Access to Scientific Information (Saggion & Ronzano, COLING 2016)
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PDF:
https://aclanthology.org/C16-3003.pdf
Presentation:
 C16-3003.Presentation.pdf