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The
high cost of manual annotation and validation of automatically
produced annotations for language data has led to the recent development
of methods to enhance the quality of automatically-produced annotations
via mechanisms such as machine learning. To date, there has been
no international forum fully dedicated to the topic, where researchers
working in different areas and different phenomena are brought
together to discuss methods and results.
This
workshop will include papers describing current work on enhancing
the results of automated annotation for linguistic phenomena and
provide both an overview and assessment of the state-of-the-art.
Papers
are solicited on any of the following topics:
- Machine
learning and other methods to enhance automatic annotation of
linguistic phenomena, including segmentation and chunking; morpho-syntactic,
syntactic, and discourse analysis; semantic annotation; entity
and event recognition; alignment of parallel translations; annotation
of dialogue, speech, gesture, and multi-modal data; etc.
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Use of information from multiple linguistic levels and/or phenomena
to enhance performance of automatic annotation software
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Machine learning and other methods for enhancing automated knowledge
acquisition (e.g, information for lexicons, ontologies, etc.)
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Evaluation and comparison of techniques to enhance the accuracy
of automatically-generated annotations, as well as discussion
of limitations
- Software
systems for optimizing annotation accuracy, and methods and
systems for optimizing "on the fly" annotation of
web and other language data
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Identification and separation of annotation that cannot be automated,
to simplify annotation enhancement by human proofreaders
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Identification and separation of applications that can tolerate
"noisy" analysis, for which imperfect automated linguistic
analysis would be appropriate
Organizers:
Nancy
Ide
Department of Computer Science
Vassar College
Poughkeepsie, New York 12604-0520 USA
email: ide@cs.vassar.edu
tel: (+1 845) 437 5988
fax: (+1 845) 437 7498 |
Eric
Atwell
School of Computing
University of Leeds
United Kingdom
email: eric@comp.leeds.ac.uk
tel: +44 (0)113 3435430
fax: +44 (0)113 3435468
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Program
Committee:
Eric
Atwell, University of Leeds (UK)
Nigel Collier, National Institute of Informatics (Japan)
Atsushi Fujii, University of Tsukuba (Japan)
Rebecca Hwa, University of Pittsburgh (USA)
Nancy Ide, Vassar College (USA)
David Lewis, David D. Lewis Consulting USA)
Miles Osborne, University of Edinburgh (UK)
Anoop Sarkar, Simon Fraser University (CA)
Mark Steedman, University of Edinburgh (UK)
Takenobu Tokunaga, Tokyo Institute of Technology (Japan)
Kiyotaka Uchimoto, National Institute of Information and Communications
Technology (Japan) |
