Natural language processing

What are the methods and applications of enabling computers to process and understand human language?

Status

Ongoing

Aims

This interest group focuses both on core natural language processing methods and tasks (such as text classification, information extraction, summarisation) and applications of natural language processing to the social sciences and humanities.

Please visit our website for more information.

How to get involved

Click here to request sign-up and join

Organisers

Researchers

Dr Elena Kochkina

Visiting Research Fellow, The Alan Turing Institute and Postdoctoral Research Assistant, QMUL

Contact info

[email protected]

External researchers

Radoslaw Kowalski, UCL
Pasquale Minervini, UCL
Andrew Moore, Lancaster University
Marek Rei, University of Cambridge

research_publications

Resolving Places, Past and Present: Toponym Resolution in Historical British Newspapers Using Multiple Resources

Newspapers and their metadata are richly geographical, not only in their distribution but also...

Coll Ardanuy, Mariona & McDonough, Katherine & Krause, Amrey & Wilson, Daniel & Hosseini, Kasra & Strien, Daniel. (2019). Resolving places, past and present: toponym resolution in historical british newspapers using multiple resources. GIR '19: Proceedings of the 13th Workshop on Geographic Information Retrieval. 1-6. 10.1145/3371140.3371143.
research_publications

Assessing the Impact of OCR Quality on Downstream NLP Tasks

A growing volume of heritage data is being digitized and made available as text...

van Strien, D.; Beelen, K.; Ardanuy, M.; Hosseini, K.; McGillivray, B. and Colavizza, G. (2020). Assessing the Impact of OCR Quality on Downstream NLP Tasks. In Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 1: ARTIDIGH, ISBN 978-989-758-395-7, pages 484-496. DOI: 10.5220/0009169004840496
research_publications

A Distributional Semantic Methodology for Enhanced Search in Historical Records: A Case Study on Smell

In this paper we present a methodology based on distributional semantic models that can...

McGregor, S. and McGillivray, B. (2018). A Distributional Semantic Methodology for Enhanced Search in Historical Records: A Case Study on Smell. Proceedings of the 14th Conference on Natural Language Processing (KONVENS 2018) Vienna, Austria, September 19-21, 2018. Austrian Academy of Sciences Press.
research_publications

Accessing and using a corpus-driven Latin Valency Lexicon

McGillivray, B. and Passarotti, M. (2015). Accessing and using a corpus-driven Latin Valency Lexicon. In Haverling, G. (Ed.), Latin linguistics in the early 21st century. Acts of the 16th international colloquium on Latin linguistics, Uppsala, June 6th-11th, 2011, Uppsala
research_publications

Metodi in linguistica computazionale latina

McGillivray, B. (2015). Metodi in linguistica computazionale latina. In Molinelli, P., Putzu, I. (Eds.), Modelli epistemologici, metodologie della ricerca e qualità del dato. Dalla linguistica storica alla sociolinguistica storica . Milan: FrancoAngeli.
research_publications

The University of Edinburgh’s Neural MT Systems for WMT17

This paper describes the University of Edinburgh's submissions to the WMT17 shared news translation...

Sennrich, R, Birch-Mayne, A, Currey, A, Germann, U, Haddow, B, Heafield, K, Miceli Barone, A & Williams, P 2017, The University of Edinburgh’s Neural MT Systems for WMT17. in EMNLP 2017: The Second Conference on Machine Translation, Volume 2: Shared Task Papers.. Association for Computational Linguistics (ACL), pp. 389-399, Proceedings of the Second Conference on Machine Translation, Copenhagen, Denmark, 7-8 September. DOI: 10.18653/v1/W17-4739