BIB-VERSION:: CS-TR-v2.0
ID:: ncstrl.dartmouthcs//TR97-319
ENTRY:: January 21, 1998
ORGANIZATION:: Dartmouth College, Computer Science
TITLE:: Generating, Visualizing and Evaluating High Quality Clusters for Information Organization
TYPE:: Technical Report (paper)
REVISION:: 1
AUTHOR:: Aslam, J.
AUTHOR:: Pelekhov, K.
AUTHOR:: Rus, Daniela
DATE:: August 1997
RETRIEVAL:: For a paper copy, email <reports@cs.dartmouth.edu>
RETRIEVAL:: For a paper copy, write to
       Technical Report Librarian
       Department of Computer Science
       Dartmouth College
       6211 Sudikoff Laboratory
       Hanover, NH 03755-3510
       USA
RETRIEVAL:: Compressed Postscript at http://www.cs.dartmouth.edu/reports/TR97-319.ps.Z
RETRIEVAL:: PDF at http://www.cs.dartmouth.edu/reports/TR97-319.pdf
ABSTRACT:: 
We present and analyze the star clustering algorithm. We discuss
an implementation of this algorithm that supports browsing and
document retrieval through information organization. We define three
parameters for evaluating a clustering algorithm to measure the topic
separation and topic aggregation achieved by the algorithm. In the
absence of benchmarks, we present a method for randomly generating
clustering data. Data from our user study shows evidence that the star
algorithm is effective for organizing information.
NOTE:: Submitted to the 1998 SIGIR Conference.
END:: ncstrl.dartmouthcs//TR97-319