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From: jair-ed@ptolemy.arc.nasa.gov
Subject: New Article, Cue Phrase Classification Using ...
Message-ID: <1996Sep17.175102.16199@ptolemy-ethernet.arc.nasa.gov>
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Date: Tue, 17 Sep 1996 17:51:02 GMT
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JAIR is pleased to announce the publication of the following article:

Litman, D.J. (1996)
  "Cue Phrase Classification Using Machine Learning", 
   Volume 5, pages 53-94.

   Available in Postscript (347K) and compressed Postscript (135K).
   For quick access via your WWW browser, use this URL:
     http://www.cs.washington.edu/research/jair/abstracts/litman96a.html
   More detailed instructions are below.

   Abstract: Cue phrases may be used in a discourse sense to explicitly
   signal discourse structure, but also in a sentential sense to convey
   semantic rather than structural information.  Correctly classifying
   cue phrases as discourse or sentential is critical in natural language
   processing systems that exploit discourse structure, e.g., for
   performing tasks such as anaphora resolution and plan recognition.
   This paper explores the use of machine learning for classifying cue
   phrases as discourse or sentential.  Two machine learning programs
   (Cgrendel and C4.5) are used to induce classification models from sets
   of pre-classified cue phrases and their features in text and speech.
   Machine learning is shown to be an effective technique for not only
   automating the generation of classification models, but also for
   improving upon previous results.  When compared to manually derived
   classification models already in the literature, the learned models
   often perform with higher accuracy and contain new linguistic insights
   into the data.  In addition, the ability to automatically construct
   classification models makes it easier to comparatively analyze the
   utility of alternative feature representations of the data.  Finally,
   the ease of retraining makes the learning approach more scalable and
   flexible than manual methods.

The article is available via:
   
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    The University of Genoa (Italy):
	ftp://ftp.mrg.dist.unige.it/pub/jair/pub/volume5/litman96a.ps

    The compressed PostScript file is named litman96a.ps.Z (135K)

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