[Corpora-List] CFP: TextGraphs-14: 14th Workshop on Graph-Based Natural Language Processing

Swapna Somasundaran swapna.sundaran at gmail.com
Fri Jan 17 21:19:37 CET 2020


*TextGraphs-14:* 14th Workshop on Graph-Based Natural Language Processing

*Venue:* COLING 2020 (https://coling2020.org)

*Location:* Barcelona, Spain

*Date:* September 14, 2020

*Website:* https://sites.google.com/view/textgraphs2020

*# Workshop Description*

TextGraphs, now going on for more than a decade, is a workshop series promoting the synergies between methods of the field of Graph Theory and Natural Language Processing.

The fourteenth edition of the TextGraphs workshop aims to extend the focus on issues and solutions for large-scale graphs, such as those derived for Web-scale knowledge acquisition or social networks, and graph-based and graph-supported machine learning and deep learning methods.

We plan to encourage the description of novel NLP problems or applications that have emerged in recent years, which can be addressed with existing and new graph-based methods. Furthermore, we also encourage research on applications of graph-based methods in the area of Semantic Web to link them to related NLP problems and applications.

*# Workshop Topics*

TextGraphs invites the submission of long and short papers on original and unpublished research covering all aspects of graph-based natural language processing. Relevant topics for the conference include, but are not limited to, the following (in alphabetical order):

Graph-based and graph-supported machine learning methods:

- Graph embeddings and their combinations with text embeddings

- Graph-based and graph-supported deep learning (e.g., graph-based recurrent and recursive networks)

- Probabilistic graphical models and structure learning methods

Graph-based methods for Information Retrieval and Extraction:

- Graph-based methods for word sense disambiguation

- Graph-based strategies for semantic relation identification

- Encoding semantic distances in graphs

- Graph-based techniques for text summarization simplification, and paraphrasing

- Graph-based techniques for document navigation and visualization

New graph-based methods for NLP applications:

- Random walk methods in graphs

- Semi-supervised graph-based methods

- Graph-based methods for applications on social networks

Graph-based methods for NLP and Semantic Web:

- Representation learning methods for knowledge graphs

- Using graphs-based methods to populate ontologies using textual data

*# Important Dates*

*May 20, 2020:* Workshop Paper Due Date

*Jun 24, 2020:* Notification of Acceptance

*Jul 11, 2020:* Camera-ready Papers Due

*Sep 14, 2020:* Workshop Date

*# Submission*

We invite submissions of up to nine (9) pages maximum, plus bibliography for long papers and four (4) pages, plus bibliography, for short papers.

The COLING’2020 templates must be used; these are provided in LaTeX and also Microsoft Word format. Submissions will only be accepted in PDF format. Deviations from the provided templates will result in rejection without review. Download the Word and LaTeX templates here: https://coling2020.org/coling2020.zip

Submit papers by the end of the deadline day (timezone is UTC-12) via our Softconf Submission Site: https://www.softconf.com/coling2020/TextGraphs/

*# Program Committee*

Željko Agić, Corti, Denmark

Prithviraj Ammanabrolu, Georgia Institute of Technology, USA

Martin Andrews, Red Dragon AI, Singapore

Tomáš Brychcín, University of West Bohemia, Czech Republic

Flavio Massimiliano Cecchini, Università Cattolica del Sacro Cuore, Italy

Tanmoy Chakraborty, Indraprastha Institute of Information Technology Delhi (IIIT-D), India

Chen Chen, Magagon Labs, USA

Jennifer D'Souza, TIB Leibniz Information Centre for Science and Technology, Germany

Stefano Faralli, University of Rome Unitelma Sapienza, Italy

Goran Glavaš, University of Mannheim, Germany

Carlos Gómez-Rodríguez, Universidade da Coruña, Spain

Binod Gyawali, Educational Testing Service, USA

Tomáš Hercig, University of West Bohemia, Czech Republic

Ming Jiang, University of Illinois at Urbana-Champaign, USA

Sammy Khalife, Ecole Polytechnique, France

Anne Lauscher, University of Mannheim, Germany

Gabor Melli, OpenGov, USA

Clayton Morrison, University of Arizona, USA

Animesh Mukherjee, IIT Kharagpur, India

Matthew Mulholland, Educational Testing Service, USA

Giannis Nikolentzos, Ecole Polytechnique, France

Enrique Noriega-Atala, The University of Arizona, USA

Jan Wira Gotama Putra, Tokyo Institute of Technology, Japan

Steffen Remus, Hamburg University, Germany

Brian Riordan, Educational Testing Service, USA

Natalie Schluter, IT University of Copenhagen, Denmark

Robert Schwarzenberg, German Research Center for Artificial Intelligence (DFKI), Germany

Rebecca Sharp, University of Arizona, USA

Konstantinos Skianis, Ecole Polytechnique, France

Saatviga Sudhahar, Healx, UK

Mihai Surdeanu, University of Arizona, USA

Yuki Tagawa, Fuji Xerox, Japan

Mokanarangan Thayaparan, University of Manchester, Sri Lanka

Antoine Tixier, Ecole Polytechnique, Palaiseau, France, France

Nicolas Turenne, BNU HKBU United International College (UIC), China

Serena Villata, Université Côte d’Azur, CNRS, Inria, I3S, France

Xiang Zhao, National University of Defense Technology, China

*# Organizers*

Dmitry Ustalov, Yandex, Russia

Swapna Somasundaran, Educational Testing Service, USA

Alexander Panchenko, Skoltech, Russia

Ioana Hulpuş, University of Mannheim, Germany

Peter Jansen, University of Arizona, USA

Fragkiskos D. Malliaros, University of Paris-Saclay, France

*Join us on Facebook:* https://www.facebook.com/groups/900711756665369/

*Follow us on Twitter:* https://twitter.com/textgraphs

*Join us on LinkedIn:* https://www.linkedin.com/groups/4882867

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