BIB-VERSION:: CS-TR-v2.0
ID:: ncstrl.dartmouthcs//TR97-324
ENTRY:: January 21, 1998
ORGANIZATION:: Dartmouth College, Computer Science
TITLE:: Computing Dense Clusters On-line for Information Organization
TYPE:: Technical Report (paper)
REVISION:: 1
AUTHOR:: Aslam, J.
AUTHOR:: Pelekhov, K.
AUTHOR:: Rus, Daniela
DATE:: October 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/TR97-324.ps.Z
RETRIEVAL:: PDF at http://www.cs.dartmouth.edu/reports/TR97-324.pdf
ABSTRACT:: 
We present and analyze the off-line star algorithm for clustering
static information systems and the on-line star algorithm for
clustering dynamic information systems. These algorithms partition a
document collection into a number of clusters that is naturally
induced by the collection. We show a lower bound on the accuracy of
the clusters produced by these algorithms.  We use the random graph
model to show that both star algorithms produce correct clusters in
time Theta(V + E). Finally, we provide data from extensive
experiments.
NOTE:: Submitted to the 1998 SIGIR Conference.
END:: ncstrl.dartmouthcs//TR97-324