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» From Comparing Clusterings to Combining Clusterings
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DIAL
2006
IEEE
167views Image Analysis» more  DIAL 2006»
14 years 3 months ago
Tree clustering for layout-based document image retrieval
We describe a system for the retrieval on the basis of layout similarity of document images belonging to collections stored in digital libraries. Layout regions are extracted and ...
Simone Marinai, Emanuele Marino, Giovanni Soda
PODS
2005
ACM
115views Database» more  PODS 2005»
14 years 9 months ago
A divide-and-merge methodology for clustering
We present a divide-and-merge methodology for clustering a set of objects that combines a top-down "divide" phase with a bottom-up "merge" phase. In contrast, ...
David Cheng, Santosh Vempala, Ravi Kannan, Grant W...
WACV
2005
IEEE
14 years 2 months ago
Image Segmentation by Unsupervised Sparse Clustering
In this paper, we present a novel solution of image segmentation based on positiveness by regarding the segmentation as one of the graph-theoretic clustering problems. On the cont...
Byoung-Ki Jeon, Yun-Beom Jung, Ki-Sang Hong
FPGA
2010
ACM
294views FPGA» more  FPGA 2010»
14 years 2 months ago
Axel: a heterogeneous cluster with FPGAs and GPUs
This paper describes a heterogeneous computer cluster called Axel. Axel contains a collection of nodes; each node can include multiple types of accelerators such as FPGAs (Field P...
Kuen Hung Tsoi, Wayne Luk
ICDM
2002
IEEE
191views Data Mining» more  ICDM 2002»
14 years 2 months ago
Iterative Clustering of High Dimensional Text Data Augmented by Local Search
The k-means algorithm with cosine similarity, also known as the spherical k-means algorithm, is a popular method for clustering document collections. However, spherical k-means ca...
Inderjit S. Dhillon, Yuqiang Guan, J. Kogan