Ontotext is Gold Sponsor of RANLP Conference 2017

Wednesday, August 30, 2017

Ontotext is Gold Sponsor of RANLP Conference 2017

Ontotext is a gold sponsor of the 11th biennial conference Recent Advances in Natural Language Processing (RANLP) that will run between September 2 and 8 in Varna, Bulgaria.

The RANLP conference has been held in Bulgaria every two years since 1995 to feature the latest developments in NLP including topics like machine learning, deep learning, text mining, sentiment analysis and many others.

This year’s event – which will welcome participants from more than 40 countries – will include two days of tutorials on September 2 and 3, the main RANLP conference and the associated Student Research Workshop on September 4-6 and five post-conference thematic workshops on September 7-8.

As a leading developer of semantic technology, Ontotext will showcase its expertise and experience in NLP and other global trends in the industry. On September 4, Andrey Tagarev, one of Ontotext’s data scientists, will present “Using big knowledge graphs and machine learning for information extraction – from financial news to scientific publications in Physics”.

The 2017 edition of RANLP will feature addresses from keynote speakers and presentations of peer-reviewed papers.

Keynote speakers and tutorial lecturers include representatives of Language Technology Group, DFKI, Ghent University,  Sapienza University of Rome, Uppsala University, Charles University, Virgen del Rocio Hospital – Seville, Mannheim University.

RANLP is organised by the Research Group in Computational Linguistics at the University of Wolverhampton, and the Department of Linguistic Modelling and Knowledge Processing in the Institute of Information and Communication Technologies at the Bulgarian Academy of Sciences.

Check out Ontotext’s webinar on best practices in text mining and see how our semantic graph database GraphDB helps organizations turn data into knowledge.



For more information, contact Doug Kimball, Chief Marketing Officer at Ontotext