NAACL HLT 2007 Workshop:
TextGraphs-2: Graph-based Methods for Natural Language Processing

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. This
workshop focuses on graph-based algorithms for natural language
processing and on the theory of graph-based methods.

Organizers:

   Chris Biemann, University of Leipzig
   Irina Matveeva, University of Chicago
   Rada Mihalcea, University of North Texas
   Dragomir Radev, University of Michigan

Full paper submissions due: January 29
Short paper submissions due: February 4

Workshop Home Page:

   http://www.textgraphs.org/ws07