In connection with COLING 2008, the 22nd International Conference on Computational Linguistics August 18-22

The workshop will be held on August 24, 2008, in conjunction with COLING in Manchester, UK.

NEW!

Invited Talk

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List of Accepted Papers

• Graph-based Clustering for Semantic Classification of Onomatopoetic Words

  Fumiyo Fukumoto and Kenichi Ichioka

• Concept-graph based Biomedical Automatic Summarization using Ontologies

  Laura Plaza, Alberto Díaz and Pablo Gervás

• How Is Meaning Grounded in Dictionary Definitions?

  Alexandre Blondin Massé, Guillaume Chicoisne, Yassine Gargouri, Stevan Harnad, Odile Marcotte and Olivier Picard

• Acquistion of the morphological structure of the lexicon based on lexical similarity and formal analogy

  Nabil Hathout

• Random Graph Model Simulations of Semantic Networks for Associative Concept Dictionaries

  Hiroyuki Akama, Jaeyoung Jung, Terry Joyce and Maki Miyake

• Learning to Map Text to Graph-based Meaning Representations via Grammar Induction

  Smaranda Muresan

• Affinity Measures Based on the Graph Laplacian

  Delip Rao and David Yarowsky

• Semantic structure from Correspondence Analysis

  Barbara McGillivray, Christer Johansson and Daniel Apollon

• Encoding Tree Pair-based Graphs in Learning Algorithms: the Textual Entailment Recognition Case

  Alessandro Moschitti and Fabio Massimo Zanzotto

Call for Papers

Recent years have shown an increased interest in bringing the field of graph theory into natural language processing. Graph theory is a well studied discipline, and so is the field of natural language processing. Traditionally, these two areas of study have been perceived as distinct, with different algorithms, different applications, and different potential end-users. However, as recent research work has shown, the two disciplines are in fact intimately connected, with a large variety of natural language processing applications finding efficient solutions within graph-theoretical frameworks.

In many NLP applications entities can be naturally represented as nodes in a graph and relations between them can be represented as edges. Recent research has shown that graph-based representations of linguistic units as diverse as words, sentences and documents give rise to novel and efficient solutions in a variety of NLP tasks, ranging from part of speech tagging, word sense disambiguation and parsing to information extraction, semantic role assignment, summarisation, sentiment analysis and up to the study of the evolutionary dynamics of language.

The TextGraphs workshop addresses a broad spectrum of research areas and brings together researchers working on problems related to the use of graph-based algorithms for natural language processing as well as on the theory of graph-based methods. Different NLP applications use different graph-based approaches, and bringing together researchers from different fields fosters the exchange of ideas. Furthermore, looking at graph-based methods from the perspective of diverse applications facilitates a discussion about the theory of graph-based methods and about the theoretical justification of the empirical results within the NLP community. This discussion is vital because further progress in graph-based NLP applications is impossible without deeper understanding of basic theoretical principles.

Starting with TextGraphs-3 we would like to have one area of graph-based NLP research as the primary topic for discussion.We intend to set this year's focus on large scale lexical acquisition and representation. Efficient graph methods can help to alleviate the acquisition bottleneck for lexicon construction and resource building. They also provide smarter representation schemes for the lexicon that facilitate fast search and word retrieval.SIGLEX endorsed our workshop proposal for COLING-08.

We invite submissions of papers on graph-based methods applied to NLP problems. Especially, we encourage submissions regarding

• Large-scale lexical acquisition using graph representations
• Graph-based representation schemes of the mental lexicon

• Graph representations for ontology learning
• Graph labeling and edge labeling for semantic representations
• Encoding semantic distances in graphs
• Graph algorithms for word sense disambiguation
• Graph methods for Information Retrieval, Information Extraction, Text Mining and Understanding
• Random walk graph methods
• Spectral graph clustering
• Small world graphs in natural language processing
• Semi-supervised graph-based methods
• Statistical network methods and analysis
• Dynamic graph representations for NLP

Organisation Committee

Irina Matveeva, Accenture Technology Labs, matveeva AT cs.uchicago.edu
Chris Biemann, Powerset, biem AT informatik.uni-leipzig.de
Monojit Choudhury, Microsoft Research, monojitc AT microsoft.com
Mona Diab,Columbia University, mdiab AT ccls.columbia.edu

Programme Committee

Eneko Agirre, University of the Basque Country
Edo Airoldi, Princeton University
Regina Barzilay, MIT
Fernando Diaz, Yahoo! Montreal
Güneş Erkan, Google
Michael Gamon, Microsoft Research
Andrew Goldberg, University of Wisconsin
Hany Hassan, IBM Egypt
Samer Hassan, University of North Texas
Gina Levow, University of Chicago
Rada Mihalcea, University of North Texas
Animesh Mukherjee, IIT Kharagpur
Dragomir Radev, University of Michigan
Uwe Quasthoff, University of Leipzig
Aitor Soroa, University of the Basque Country
Hans Friedrich Witschel, University of Leipzig
Fabio Massimo Zanzotto, University of Rome "Tor Vergata"
Thorsten Zesch, University of Darmstadt

Important Dates, note the Deadline Extension

Regular paper submissions	May 12, 2008 (23:59 GMT -12:00)
Short paper submissions	May 19, 2008
Notification of acceptance	June 6, 2008
Camera-ready papers	July 1, 2008
Workshop	August 24, 2008

Author Instructions

Submissions will consist of regular full papers of max. 8 pages and short papers of max. 4 pages, formatted following the COLING 2008 formatting guidelines. Papers should be submitted using the Online Submission Form. The review process double blind, please anonymise your submission. For any questions, please contact one of the organisers.

Previous Workshops

The TextGraphs-3 workshop builds on the success of the first and second TextGraphs workshops:
TextGraphs-1 at HLT-NAACL 2006, for proceedings click here
TextGraphs-2 at HLT-NAACL 2007, for proceedings click here
There is the tutorial Graph-based Algorithms for Information Retrieval and Natural Language Processing from HLT-NAACL 2006 by Dragomir Radev and Rada Mihalcea.