Call for Participation
Graph-based Algorithms for Natural Language Processing
http://www.textgraphs.org/ws06
A workshop to be held at HLT-NAACL 2006
New York City
June 9, 2006
Registration site: http://nlp.cs.nyu.edu/hlt-naacl06/
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.
The goal of this workshop is to provide a forum for researchers
working on problems related to the use of graph-based algorithms for
natural language processing. The workshop is expected to bring
together people working on areas as diverse as lexical semantics, text
summarization, text mining, ontology construction, clustering and
learning, connected by the common underlying theme consisting of the
use of graph-theoretical methods for text processing tasks.
Registration:
Invited talk:
Lillian Lee, Cornell University
List of accepted papers:
A Graphical Framework for Contextual Search and Name Disambiguation in
Email
Einat Minkov, William Cohen and Andrew Ng
Graph Based Semi-Supervised Approach for Information Extraction
Hany Hassan, Ahmed Hassan and Sara Noeman
Graph-Based Text Representation for Novelty Detection
Michael Gamon
Measuring Aboutness of an Entity in a Text
Marie-Francine Moens
A Study of Two Graph Algorithms in Topic-driven Summarization
Vivi Nastase and Stan Szpakowicz
Similarity between Pairs of Co-indexed Trees for Textual Entailment
Recognition
Fabio Massimo Zanzotto and Alessandro Moschitti
Learning of Graph-based Question Answering Rules
Diego Molla
Seeing stars when there aren't many stars: Graph-based semi-supervised
learning for sentiment categorization
Andrew Goldberg and Xiaojin Zhu
Random-Walk Term Weighting for Improved Text Classification
Samer Hassan and Carmen Banea
Graph-based Generalized Latent Semantic Analysis for Document
Representation
Irina Matveeva and Gina-Anne Levow
Synonym Extraction Using a Semantic Distance on a Dictionary
Philippe Muller, Nabil Hathout and Bruno Gaume
Chinese Whispers - an Efficient Graph Clustering Algorithm and its
Application to Natural Language Processing Problems
Chris Biemann
Matching syntactic-semantic graphs for semantic relation assignment
Vivi Nastase and Stan Szpakowicz
Evaluating and optimizing the parameters of an unsupervised graph-based
WSD algorithm
Eneko Agirre, David Martmnez, Oier Lspez de Lacalle and Aitor Soroa
Context Comparison as a Minimum Cost Flow Problem
Vivian Tsang and Suzanne Stevenson
Co-chairs:
Rada Mihalcea, University of North Texas
Dragomir Radev, University of Michigan
Program committee:
Lada Adamic, University of Michigan
Razvan Bunescu, University of Texas at Austin
Timothy Chklovski, USC / Information Sciences Institute
Diane Cook, University of Texas at Arlington
Inderjit Dhillon, University of Texas at Austin
Beate Dorow, Stuttgart University, Germany
Gael Dias, Universidade da Beira Interior, Portugal
Kevin Gee, University of Texas at Arlington
Gunes Erkan, University of Michigan
Lise Getoor, University of Maryland
John Lafferty, Carnegie Mellon University
Lillian Lee, Cornell University
Andrew McCallum, University of Massachusetts
Bo Pang, Cornell University
Patrick Pantel, USC / Information Sciences Institute
Paul Tarau, University of North Texas
Simone Teufel, University of Cambridge
Lucy Vanderwende, Microsoft Research
Florian Wolf, F-W Consulting
Dominic Widdows, Maya Design
Hongyuan Zha, Penn State
Xiaojin Zhu, University of Wisconsin
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