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From: jair-ed@ptolemy.arc.nasa.gov
Subject: New Article, MUSE CSP: An Extension ...
Message-ID: <1996Dec3.183052.26509@ptolemy-ethernet.arc.nasa.gov>
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Date: Tue, 3 Dec 1996 18:30:52 GMT
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JAIR is pleased to announce the publication of the following article:

Helzerman, R.A and Harper, M.P. (1996)
  "MUSE CSP: An Extension to the Constraint Satisfaction Problem", 
   Volume 5, pages 239-288.

   Available in HTML, Postscript (2.1M) and compressed Postscript (439K).
   For quick access via your WWW browser, use this URL:
     http://www.cs.washington.edu/research/jair/abstracts/helzerman96a.html
   More detailed instructions are below.

   Abstract: This paper describes an extension to the constraint
   satisfaction problem (CSP) called MUSE CSP (MUltiply SEgmented
   Constraint Satisfaction Problem).  This extension is especially useful
   for those problems which segment into multiple sets of partially
   shared variables.  Such problems arise naturally in signal processing
   applications including computer vision, speech processing, and
   handwriting recognition.  For these applications, it is often
   difficult to segment the data in only one way given the low-level
   information utilized by the segmentation algorithms.  MUSE CSP can be
   used to compactly represent several similar instances of the
   constraint satisfaction problem.  If multiple instances of a CSP have
   some common variables which have the same domains and constraints,
   then they can be combined into a single instance of a MUSE CSP,
   reducing the work required to apply the constraints.  We introduce the
   concepts of MUSE node consistency, MUSE arc consistency, and MUSE path
   consistency. We then demonstrate how MUSE CSP can be used to compactly
   represent lexically ambiguous sentences and the multiple sentence
   hypotheses that are often generated by speech recognition algorithms
   so that grammar constraints can be used to provide parses for all
   syntactically correct sentences.  Algorithms for MUSE arc and path
   consistency are provided.  Finally, we discuss how to create a MUSE
   CSP from a set of CSPs which are labeled to indicate when the same
   variable is shared by more than a single CSP.

The article is available via:
   
 -- comp.ai.jair.papers (also see comp.ai.jair.announce)

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    For direct access to this article and related files try:
       http://www.cs.washington.edu/research/jair/abstracts/helzerman96a.html

 -- Anonymous FTP from either of the two sites below.

    Carnegie-Mellon University (USA):
	ftp://ftp.cs.cmu.edu/project/jair/volume5/helzerman96a.ps
    The University of Genoa (Italy):
	ftp://ftp.mrg.dist.unige.it/pub/jair/pub/volume5/helzerman96a.ps

    The compressed PostScript file is named helzerman96a.ps.Z (439K)

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