Mechanisms of Partial Supervision in Rough Clustering Approaches

Authors:
Rafael Falcón;Gwanggil Jeon;Kangjun Lee;Rafael Bello;J. Jeong
Affiliations:
School of Information Tech. & Engineering, University of Ottawa, Canada;Dept. of Electronics and Computer Eng., Hanyang University, Korea;Dept. of Electronics and Computer Eng., Hanyang University, Korea;Computer Science Department, Central University of Las Villas (UCLV), Cuba;Dept. of Electronics and Computer Eng., Hanyang University, Korea
Venue:
RSKT '09 Proceedings of the 4th International Conference on Rough Sets and Knowledge Technology
Year:
2009

Citing 5
Cited 0

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Abstract

We bring two rough-set-based clustering algorithms into the framework of partially supervised clustering. A mechanism of partial supervision relying on either qualitative or quantitative information about memberships of patterns to clusters is envisioned. Allowing such knowledge-based hints to play an active role in the clustering process has proved to be highly beneficial, according to our empirical results. Other existing rough clustering techniques can successfully incorporate this type of auxiliary information with little computational effort.