International Journal of Computational Intelligence Systems

Volume 3, Issue 6, December 2010, Pages 770 - 785

Clustering with Instance and Attribute Level Side Information

Authors
Jinlong Wang, Shunyao Wu, Gang Li
Corresponding Author
Jinlong Wang
Received 16 February 2010, Accepted 26 October 2010, Available Online 1 December 2010.
DOI
10.2991/ijcis.2010.3.6.8How to use a DOI?
Keywords
Data mining, Clustering, Semi-supervised learning, Constraints
Abstract

Selecting a suitable proximity measure is one of the fundamental tasks in clustering. How to effectively utilize all available side information, including the instance level information in the form of pair-wise constraints, and the attribute level information in the form of attribute order preferences, is an essential problem in metric learning. In this paper, we propose a learning framework in which both the pair-wise constraints and the attribute order preferences can be incorporated simultaneously. The theory behind it and the related parameter adjusting technique have been described in details. Experimental results on benchmark data sets demonstrate the effectiveness of proposed method.

Copyright
© 2010, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

Journal
International Journal of Computational Intelligence Systems
Volume-Issue
3 - 6
Pages
770 - 785
Publication Date
2010/12/01
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
10.2991/ijcis.2010.3.6.8How to use a DOI?
Copyright
© 2010, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - JOUR
AU  - Jinlong Wang
AU  - Shunyao Wu
AU  - Gang Li
PY  - 2010
DA  - 2010/12/01
TI  - Clustering with Instance and Attribute Level Side Information
JO  - International Journal of Computational Intelligence Systems
SP  - 770
EP  - 785
VL  - 3
IS  - 6
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.2010.3.6.8
DO  - 10.2991/ijcis.2010.3.6.8
ID  - Wang2010
ER  -