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TextGraphs 2020 : 14th Workshop on Graph-Based Natural Language Processing (TextGraphs-14)Conference Series : Graph-based Methods for Natural Language Processing | |||||||||||||||
Link: https://sites.google.com/view/textgraphs2020/ | |||||||||||||||
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Call For Papers | |||||||||||||||
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 # Workshop Topics TextGraphs invites the submission of long and short papers on original and unpublished research covering all aspects of graph-based natural language processing.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 13, 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 # Contact Please direct all questions and inquiries to our official e-mail address (textgraphsOC@gmail.com) or contact any of the organizers via their individual emails. 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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