TextGraphs 2012 - TextGraphs-7: Graph-based Methods for Natural Language Processing

TextGraphs is in its seventh edition! This shows that the disciplines graph theoretic models and computational linguistics, are naturally connected, with a large variety of Natural Language Processing (NLP) applications adopting efficient and elegant solutions from graph-theoretical framework.
The TextGraphs workshops series brings together researchers interested in Graph Theory applied to Natural Language Processing and provides an environment for further integration of graph-based solutions into NLP tasks. The workshops encourage discussions about theoretical justifications from Graph Theory that explain empirical results obtained in the NLP community. As a consequence, a deeper understanding of new theories of graph-based algorithms is likely to help to create new approaches and widen the usage of graphs for NLP applications.
Suggested topics
We invite submissions on the following (but not limited to) general topics:
Graph-based methods for Information Retrieval, Information Extraction and Text Mining
Graph-based methods for word sense disambiguation,
Graph-based representations for ontology learning,
Graph-based strategies for semantic relations identification,
Encoding semantic distances in graphs,
Graph-based techniques for document navigation and visualization, etc;
New graph-based methods for NLP applications
Random walk methods in graphs,
Spectral graph clustering,
Graph-based strategies for semantic relations identification,
Semi-supervised graph-based methods,
Methods and analyses for statistical networks,
Small world graphs,
Dynamic graph representations,
Topological and pretopological analysis of graphs, etc;
Graph-based methods for applications on social networks
Rumor proliferation,
E-reputation,
Multiple identity detection,
Language dynamics studies,
Surveillance systems, etc.