Constrained Partitional Clustering of Text Data: An Overview - Text Mining: Classification, Clustering, and Applications - page 187

[34] T. Lange, M. H. C. Law, A. K. Jain, and J. M. Buhmann. Learning with
constrained and unlabeled data. In CVPR , pages 731-738. San Diego,
CA, 2005.
[35] Z. Lu and T. Leen. Semi-supervised learning with penalized probabilistic
clustering. In Advances in Neural Information Processing Systems , 2005.
[36] Z. Lu and T. K. Leen. Semi-supervised learning with penalized prob-
abilistic clustering. In Advances in Neural Information Processing Sys-
tems 17 , 2005.
[37] M. Meila. Comparing clusterings by the variation of information. In
Proceedings of the 16th Annual Conference on Computational Learning
Theory , pages 173-187, 2003.
[38] R. M. Neal and G. E. Hinton. A view of the EM algorithm that justifies
incremental, sparse, and other variants. In Michael I. Jordan, editor,
Learning in Graphical Models , pages 355-368. MIT Press, 1998.
[39] D. Pelleg and D. Baras. K-means with large and noisy constraint sets.
In ECML , 2007.
[40] M. Sahami. Personal communication, September 2007.
[41] G. Salton and M. J. McGill. Introduction to Modern Information Re-
trieval . McGraw-Hill, New York, 1983.
[42] M. Seeger. Learning with labeled and unlabeled data, 2000.
[43] E. Segal, H. Wang, and D. Koller. Discovering molecular pathways from
protein interaction and gene expression data. Bioinformatics , 19:i264-
i272, July 2003.
[44] J. Sinkkonen and S. Kaski. Semisupervised clustering based on condi-
tional distributions in an auxiliary space. Technical Report A60, Helsinki
University of Technology, 2000.
[45] A. Strehl, J. Ghosh, and R. Mooney. Impact of similarity measures
on web-page clustering. In Workshop on Artificial Intelligence for Web
Search (AAAI 2000) , pages 58-64, July 2000.
[46] K. Wagstaff and C. Cardie. Clustering with instance-level constraints.
In Proceedings of the Seventeenth International Conference on Machine
Learning , pages 1103-1110, Palo Alto, CA, 2000. Morgan Kaufmann.
[47] K. Wagstaff, C. Cardie, S. Rogers, and S. Schroedl. Constrained K-
Means clustering with background knowledge. In Proceedings of ICML ,
pages 577-584, 2001.
[48] E. P. Xing, A. Y. Ng, M. I. Jordan, and S. Russell. Distance metric
learning, with application to clustering with side-information. In NIPS
15 , 2003.