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» From Comparing Clusterings to Combining Clusterings
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ECCV
2010
Springer
13 years 11 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...
INTERACT
2003
13 years 10 months ago
Clustering the Information Space Using Top-Ranking Sentences: A Study of User Interaction
: By considering sentences selected by a query-biased sentence extraction model from the top-retrieved documents, we create a personalised information space which is characterised ...
Anastasios Tombros, Joemon M. Jose, Ian Ruthven, R...
EACL
2003
ACL Anthology
13 years 10 months ago
Combining Distributional and Morphological Information for Part of Speech Induction
In this paper we discuss algorithms for clustering words into classes from unlabelled text using unsupervised algorithms, based on distributional and morphological information. We...
Alexander Clark
ICPR
2008
IEEE
14 years 3 months ago
Adaptive selection of non-target cluster centers for K-means tracker
Hua et al. have proposed a stable and efficient tracking algorithm called “K-means tracker”[2, 3, 5]. This paper describes an adaptive non-target cluster center selection met...
Hiroshi Oike, Haiyuan Wu, Toshikazu Wada
CCGRID
2007
IEEE
14 years 3 months ago
Virtual Clusters on the Fly - Fast, Scalable, and Flexible Installation
One of the advantages in virtualized computing clusters compared to traditional shared HPC environments is their ability to accommodate user-specific system customization. Howeve...
Hideo Nishimura, Naoya Maruyama, Satoshi Matsuoka