Call for Papers
"Theoretical Advances in Data Clustering"
Special Issue of Machine Learning journal
Guest Editors:
Nina Mishra, HP Labs/Stanford University
Rajeev Motwani, Stanford University
Data clustering, the problem of grouping similar objects together,
has attracted significant practical attention due to modern applications
like web document clustering, click stream analysis, multimedia
applications, and telecommunication records. The field has experienced
a corresponding theoretical surge due to recent algorithmic discoveries
and novel methods of modeling the clustering problem. In this special
issue,
we seek papers that document theoretical advances related to
data clustering. Topics of interest include, but are not limited to:
- approximation/randomized algorithms
- graph-based clustering
- spectral clustering
- dimension reduction techniques
- dense region identification
- Bayesian clustering
- statistical/machine-learning theory
- testing clusterability
- clustering large datasets
- clustering dynamic datasets, like data streams
- mixture modeling
- conceptual clustering
Rigorous papers supported with empirical case studies are also welcome.
Review Criteria
Submissions must not have appeared in, nor be under consideration by
other journals. Exceptional surveys will be considered.
Except in extraordinary circumstances, submissions should
not exceed 35 pages (journal-formatted pages), excluding
abstract/references.
Submission Process
Only electronic submissions will be accepted. Instructions
for submission can be found at
http://www.cs.ualberta.ca/~holte/mlj/initialsubmission.pdf
In the text of your electronic submission, please explicitly
state that the paper is for this special issue.
In addition to submitting the paper to [EMAIL PROTECTED], please
also submit to [EMAIL PROTECTED]
Important Dates
Dec 6, 2002 Abstract submission.
Dec 13, 2002 Full submissions should be received.
May 27, 2003 Decisions sent to authors; papers accepted
with no more than minor revisions accepted to
the special issue.
Dec 27, 2003 Final versions of accepted papers should be received
in the format specified for full submissions, using
Kluwer style guidelines.
An online version of this call for papers can be found at:
http://www.hpl.hp.com/personal/Nina_Mishra/MLJ-clustering.html
