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» Clustering by pattern similarity in large data sets
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KDD
2007
ACM
152views Data Mining» more  KDD 2007»
16 years 7 months ago
Efficient incremental constrained clustering
Clustering with constraints is an emerging area of data mining research. However, most work assumes that the constraints are given as one large batch. In this paper we explore the...
Ian Davidson, S. S. Ravi, Martin Ester
SDM
2008
SIAM
176views Data Mining» more  SDM 2008»
15 years 8 months ago
A General Model for Multiple View Unsupervised Learning
Multiple view data, which have multiple representations from different feature spaces or graph spaces, arise in various data mining applications such as information retrieval, bio...
Bo Long, Philip S. Yu, Zhongfei (Mark) Zhang
COLT
2004
Springer
15 years 12 months ago
Regularization and Semi-supervised Learning on Large Graphs
We consider the problem of labeling a partially labeled graph. This setting may arise in a number of situations from survey sampling to information retrieval to pattern recognition...
Mikhail Belkin, Irina Matveeva, Partha Niyogi
DEXA
2003
Springer
193views Database» more  DEXA 2003»
15 years 11 months ago
Supporting KDD Applications by the k-Nearest Neighbor Join
Abstract. The similarity join has become an important database primitive to support similarity search and data mining. A similarity join combines two sets of complex objects such t...
Christian Böhm, Florian Krebs
GFKL
2007
Springer
123views Data Mining» more  GFKL 2007»
16 years 20 days ago
Projecting Dialect Distances to Geography: Bootstrap Clustering vs. Noisy Clustering
Abstract. Dialectometry produces aggregate distance matrices in which a distance is specified for each pair of sites. By projecting groups obtained by clustering onto geography on...
John Nerbonne, Peter Kleiweg, Wilbert Heeringa, Fr...