NLP in the Era of Big Data, Deep Learning, and Post Truth


Language and Computation Courses


NLP in the Era of Big Data, Deep Learning, and Post Truth,
Preslav Nakov (Qatar Computing Research Institute, HBKU, Qatar), Ahmed Ali (Qatar Computing Research Institute, HBKU), Irina Temnikova (Sofia University), Georgi Georgiev (Leanplum), Lluis Marquez (Amazon), Shafiq Joty (Nanyang Technological University), and Ivan Koychev (Sofia University)

Week 2, 11:00 – 12:30, Room Mirror Hall, Floor 2

Here is the Website of the Workshop.

Selected papers that have been presented at the workshop will be invited to submit a full version of the paper to the Cybernetics and Information Technologies journal, which is indexed by SCOPUS, SJR, and some other databases:

The Cybernetics and Information Technologies Journal

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.