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» Clustering with Instance-level Constraints
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ICASSP
2010
IEEE
13 years 8 months ago
Multiplicative update rules for nonnegative matrix factorization with co-occurrence constraints
Nonnegative matrix factorization (NMF) is a widely-used tool for obtaining low-rank approximations of nonnegative data such as digital images, audio signals, textual data, financ...
Steven K. Tjoa, K. J. Ray Liu
CICLING
2009
Springer
14 years 8 months ago
Semi-supervised Clustering for Word Instances and Its Effect on Word Sense Disambiguation
We propose a supervised word sense disambiguation (WSD) system that uses features obtained from clustering results of word instances. Our approach is novel in that we employ semi-s...
Kazunari Sugiyama, Manabu Okumura
DAWAK
2004
Springer
14 years 1 months ago
SCLOPE: An Algorithm for Clustering Data Streams of Categorical Attributes
Clustering is a difficult problem especially when we consider the task in the context of a data stream of categorical attributes. In this paper, we propose SCLOPE, a novel algorith...
Kok-Leong Ong, Wenyuan Li, Wee Keong Ng, Ee-Peng L...
IDA
2003
Springer
14 years 1 months ago
Fuzzy Clustering Based Segmentation of Time-Series
The segmentation of time-series is a constrained clustering problem: the data points should be grouped by their similarity, but with the constraint that all points in a cluster mus...
János Abonyi, Balazs Feil, Sandor Z. N&eacu...
ECCV
2010
Springer
13 years 10 months ago
Learning Shape Segmentation Using Constrained Spectral Clustering and Probabilistic Label Transfer
We propose a spectral learning approach to shape segmentation. The method is composed of a constrained spectral clustering algorithm that is used to supervise the segmentation of a...