TY - GEN
T1 - Identifying structure across prepartitioned data
AU - Marx, Zvika
AU - Dagan, Ido
AU - Shamir, Eli
PY - 2004
Y1 - 2004
N2 - We propose an information-theoretic clustering approach that incorporates a pre-known partition of the data, aiming to identify common clusters that cut across the given partition. In the standard clustering setting the formation of clusters is guided by a single source of feature information. The newly utilized pre-partition factor introduces an additional bias that counterbalances the impact of the features whenever they become correlated with this known partition. The resulting algorithmic framework was applied successfully to synthetic data, as well as to identifying text-based cross-religion correspondences.
AB - We propose an information-theoretic clustering approach that incorporates a pre-known partition of the data, aiming to identify common clusters that cut across the given partition. In the standard clustering setting the formation of clusters is guided by a single source of feature information. The newly utilized pre-partition factor introduces an additional bias that counterbalances the impact of the features whenever they become correlated with this known partition. The resulting algorithmic framework was applied successfully to synthetic data, as well as to identifying text-based cross-religion correspondences.
UR - http://www.scopus.com/inward/record.url?scp=80053266317&partnerID=8YFLogxK
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AN - SCOPUS:80053266317
SN - 0262201526
SN - 9780262201520
T3 - Advances in Neural Information Processing Systems
BT - Advances in Neural Information Processing Systems 16 - Proceedings of the 2003 Conference, NIPS 2003
PB - Neural information processing systems foundation
T2 - 17th Annual Conference on Neural Information Processing Systems, NIPS 2003
Y2 - 8 December 2003 through 13 December 2003
ER -