NLP-Era 2018 : ESSLLI-2018 Workshop on NLP in the Era of Big Data, Deep Learning, and Post Truth
Call For Papers
CALL FOR EXTENDED ABSTRACTS
"NLP in the Era of Big Data, Deep Learning, and Post Truth"
Workshop at ESSLLI 2018
August 13-17, 2018
Recent years have seen fast advances of the field of Natural Language Processing (NLP) due to the simultaneous influence of two revolutionary forces: Big Data and Deep Learning. The aim of using large corpora has been prominent in NLP since an earlier statistical, corpus-based revolution of the 1990s. Indeed, in corpus-based NLP size does matter, and researchers have been exploring corpora as large as the entire Web; now this abundance of data has enabled the return of Neural Networks and the rise of Deep Learning. More recently, we have further seen the rise of Big Data with its 3Vs: Volume, Velocity, and Variety. Even more recently, with the spread of fake news, it has been suggested that a fourth V should be considered: Veracity.
The workshop welcomes work presenting new developments in applying NLP for solving problems related to Big Data, Deep Learning, and Veracity. We also invite discussion about the impact of these revolutionary forces on the field of NLP as a whole.
The workshop will be held during the whole second week of the 30th edition of ESSLLI (European Summer School in Logic, Language and Information) August 13 - 17, 2018.
The workshop invites extended abstracts related to but not limited to the following:
- Big Data for NLP
- Web as a corpus
- Deep learning for NLP
- Automatic fact checking, stance detection, bias detection
- Multi-modality: combining NLP, speech, images, and/or video
- Language varieties and dialect processing
- Work at the intersection of the above areas
- Position papers discussing the impact of the above on NLP
Abstract submission: April 16, 2018
Author notification: May 18, 2018
Camera-ready version: June 4, 2018
Deadlines are midnight Pacific Standard Time (UTC−8).
Extended abstracts should present original, unpublished research and/or implementation results. We invite extended abstracts of up to two pages, excluding references. All submissions will be electronic and in PDF format, sent via the EasyChair system.
Submissions will be anonymous. Information about the author(s) and other identifying information such as obvious self-references (e.g., "We have shown in ") and financial or personal acknowledgements should be omitted in the submitted abstracts whenever feasible.
Extended abstracts may contain a clearly marked appendix and data files to support its claims. While reviewers are urged to consult this extra material for better comprehension, it is at their discretion whether they do so. Such extra material should also be anonymized to the extent feasible.
Papers should be submitted through the EasyChair system at: https://easychair.org/conferences/?conf=esslli2018nlpera
Preslav Nakov (Qatar Computing Research Institute, HBKU)
Ahmed Ali (Qatar Computing Research Institute, HBKU)
Irina Temnikova (Sofia University)
Georgi Georgiev (Ontotext)
Lluís Màrquez (Amazon Research)
Shafiq Joty (Nanyang Technological University)
Ramy Baly, MIT & Qatar Computing Research Institute, HBKU (USA&Qatar)
Mona Diab, Columbia University (USA)
Noura Farra, Columbia University (USA)
Shervin Malmasi, Harvard Medical School (United States)
Diarmuid Ó Séaghdha, University of Cambridge (UK)
Petya Osenova, Bulgarian Academy of Sciences (Bulgaria)
Sara Rosenthal, IBM T. J. Watson (USA)
Serge Sharoff, University of Leeds (UK)
Kiril Simov, Bulgarian Academy of Sciences (Bulgaria)
Sara Stymne, Uppsala University (Sweden)
Stan Szpakowicz, University of Ottawa (Canada)
Aline Villavicencio, Federal University of Rio Grande do Sul (Brazil)
Andreas Vlachos, University of Sheffield (UK)
Pidong Wang, Machine Zone Inc. (USA)
Marcos Zampieri, University of Wolverhampton (UK)