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Date: Wednesday, 20-Nov-96 19:59:56 GMT
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<TITLE>The Case-Based Reasoning Group</TITLE>
<h1>The Case-Based Reasoning Group</h1>
<hr>
<!WA0><img src="http://cbr-www.cs.umass.edu/images/cbr-logo.gif">
<hr>
<p>
<h2>Welcome to the CBR Web Server</h2>
<p>
The Case-Based Reasoning Group is part of the <!WA1><a
href="http://www.cs.umass.edu/"> Department of Computer Science</a> at
the <!WA2><a href="http://www.cs.umass.edu/rcfdocs/newhome/index.html">
University of Massachusetts at Amherst</a>.  You can find specific
information here about our <!WA3><a
href="http://cbr-www.cs.umass.edu/research-summaries.html">research</a>, <!WA4><a
href="http://cbr-www.cs.umass.edu/publications.html">publications</a>, <!WA5><a
href="http://cbr-www.cs.umass.edu/abstracts.html">abstracts</a>, and <!WA6><a
href="http://cbr-www.cs.umass.edu/directory.html">personnel</a>.
<p>
<h2>Purpose</h2>
<p>
Research in Professor Edwina Rissland's CBR Group deals with
case-based reasoning (CBR), AI and Legal Reasoning, CBR and machine
learning, CBR and information retrieval, and CBR and
scheduling. Current research projects include projects to investigate
the use of multiple case representation and indexing schemes in
precedent-based CBR, the effect of high level reasoning goals on
supporting CBR tasks and vice versa in a mixed paradigm
blackboard-based architecture, the use of CBR for generation of
retrieval strategies in the context of information retrieval, and
the automatic selection of parameters for dynamic scheduling problems.
<p>
<h2><!WA7><a href="http://cbr-www.cs.umass.edu/research-summaries.html">Research</a></h2>
<ul>

<li><!WA8><a href="http://cbr-www.cs.umass.edu/research-summaries.html#CBR-IR">CBR-IR</a> - a case-based
information retrieval system that uses CBR-determined relevant cases
to generate queries that are submitted to INQUERY.

<li><!WA9><a href="http://cbr-www.cs.umass.edu/research-summaries.html#BankXX">BankXX</a> - the first
CBR system using the framework of heuristic best-first search to guide
retrieval of cases and other pertinent knowledge for adversarial argument

<li><!WA10><a href="http://cbr-www.cs.umass.edu/research-summaries.html#FRANK">FRANK</a> - a
blackboard-based architecture to create diagnostic reports tailored to
the user's prescribed goals and specified report type

<li><!WA11><a href="http://cbr-www.cs.umass.edu/research-summaries.html#OFF-BROADWAY">OFF-BROADWAY</a> -
a case retrieval and classification system that learns a set of
distinguished cases (actual prototypes) that have demonstrated
classification power

<li><!WA12><a href="http://cbr-www.cs.umass.edu/research-summaries.html#BROADWAY">BROADWAY</a> - a CBR
system whose retrieval is relative to the type of case.

<li><!WA13><a href="http://cbr-www.cs.umass.edu/research-summaries.html#CABOT">CABOT</a> - a project in
case-based search that developed an inductive learning algorithm that
adjusts its retrieval and adaptation mechanisms

<li><!WA14><a href="http://cbr-www.cs.umass.edu/research-summaries.html#CABARET/ID5">CABARET/ID5</a> - a
CBR/ML project that investigated the selection of training instances
using characterizations of cases (e.g., most on-point, trumping, best)
employed in our other CBR systems

<li><!WA15><a href="http://cbr-www.cs.umass.edu/research-summaries.html#CABARET">CABARET</a> - the first
mixed paradigm (CBR-RBR) hybrid

<li><!WA16><a href="http://cbr-www.cs.umass.edu/research-summaries.html#HYPO">HYPO</a> - the first precedent-based CBR system

</ul>
<hr>
<!WA17><a href="http://cbr-www.cs.umass.edu/stats/summary.html">
<!WA18><img src="http://cbr-www.cs.umass.edu/stats/recent-chip.gif"> Server traffic summary reports</a>
<hr>
<p>
<address><!WA19><a href="http://cbr-www.cs.umass.edu/cbr-www-admin.html">
CBR Web Server Administrator</a>
</address>
<i>Last Update: 2/17/95</i>