No subject

[Ron Sun]

Paper available:
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title: STRUCTURING KNOWLEDGE IN VAGUE DOMAINs

               Ron Sun
           Department of Computer Science
           College of Engineering
           The University of Alabama
           Tuscaloosa, AL 35487
           rsun at cs.ua.edu

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to appear in: IEEE Transaction on Knowledge and Data Engineering
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In this paper, we propose a model for structuring  knowledge
in vague and continuous domains where similarity plays
a role in coming up with plausible inferences.  The model 
consists of two levels, one of which is an inference network 
with nodes representing concepts and links representing rules 
connecting concepts, and the other is a microfeature based 
replica of the first level.  Based on the interaction between 
the concept nodes and microfeature nodes in the model, 
inferences are facilitated and knowledge not explicitly encoded 
in a system can be deduced via mixed similarity matching and rule 
application.  The model is able to take account of many important 
desiderata of plausible reasoning, and produces sensible conclusions 
accordingly.  Examples will be presented to illustrate the utility 
of the model in structuring knowledge to enable useful inferences
to be carried out in several domains.

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* It is FTPable from archive.cis.ohio-state.edu 
  in: pub/neuroprose (Courtesy of Jordan Pollack)
* No hardcopy available.

* FTP procedure:
        unix> ftp archive.cis.ohio-state.edu (or 128.146.8.52)
        Name: anonymous
        Password: 
        ftp> cd pub/neuroprose
        ftp> binary
        ftp> get sun.vague.ps.Z
        ftp> quit
        unix> uncompress sun.vague.ps.Z
        unix> lpr sun.vague.ps (or however you print postscript)