NLP in the Era of Big Data, Deep Learning, and Post Truth
NLPEBDDLPT 2018
- Event Date: 2018-08-13 ~ 2018-08-17
- Submission Date: 2018-04-02
- Location: Sofia, Bulgaria
CALL FOR EXTENDED ABSTRACTS
NLP in the Era of Big Data, Deep Learning, and Post Truth
Workshop at ESSLLI 2018
August 13-17, 2018
INTRODUCTION
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.
TOPICS
The workshop invites extended abstracts related to but not limited to
the following:
- Big Data for NLP
- deep learning for NLP
- automatic fact checking, stance detection, bias detection
- Web as a corpus
- work at the intersection of the above areas
- position papers discussing the impact of the above on NLP
IMPORTANT DATES
Abstract submission: April 2, 2018
Author notification: May 2, 2018
Camera-ready version: May 14, 2018
Deadlines are midnight Pacific Standard Time (UTC−8).
SUBMISSIONS
Extended abstracts should present original, unpublished research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. Information about
the author(s) and other identifying information such as obvious self-
references and financial or personal acknowledgments 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.
Organizers
Preslav Nakov (Qatar Computing Research Institute, HBKU)
Ahmed Ali (Qatar Computing Research Institute, HBKU)
Irina Temnikova (Sofia University)
Georgi Georgiev (Ontotext)
Lluis Marquez (Amazon)
Shafiq Joty (Nanyang Technological University)
Ivan Koychev (Sofia University)
NLP in the Era of Big Data, Deep Learning, and Post Truth
Workshop at ESSLLI 2018
August 13-17, 2018
INTRODUCTION
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.
TOPICS
The workshop invites extended abstracts related to but not limited to
the following:
- Big Data for NLP
- deep learning for NLP
- automatic fact checking, stance detection, bias detection
- Web as a corpus
- work at the intersection of the above areas
- position papers discussing the impact of the above on NLP
IMPORTANT DATES
Abstract submission: April 2, 2018
Author notification: May 2, 2018
Camera-ready version: May 14, 2018
Deadlines are midnight Pacific Standard Time (UTC−8).
SUBMISSIONS
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. Information about
the author(s) and other identifying information such as obvious self-
references and financial or personal acknowledgments 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.
Organizers
Preslav Nakov (Qatar Computing Research Institute, HBKU)
Ahmed Ali (Qatar Computing Research Institute, HBKU)
Irina Temnikova (Sofia University)
Georgi Georgiev (Ontotext)
Lluis Marquez (Amazon)
Shafiq Joty (Nanyang Technological University)
Ivan Koychev (Sofia University)
Journal Promotion
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| Acta Koreana (Acta Koreana) |
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| Acta Via Serica (AVS) |
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| Computers and Concrete (CAC) |
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| Journal of Information Processing Systems (JIPS) |
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| Journal of Smart Tourism (Smart Tourism) |
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| Wind and Structures, An International Journal (Wind and Structures) |
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