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» Robust Hierarchical Clustering
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ICDM
2007
IEEE
179views Data Mining» more  ICDM 2007»
14 years 4 months ago
GDClust: A Graph-Based Document Clustering Technique
This paper introduces a new technique of document clustering based on frequent senses. The proposed system, GDClust (Graph-Based Document Clustering) works with frequent senses ra...
M. Shahriar Hossain, Rafal A. Angryk
PODS
2005
ACM
115views Database» more  PODS 2005»
14 years 10 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...
WEBI
2009
Springer
14 years 4 months ago
Full-Subtopic Retrieval with Keyphrase-Based Search Results Clustering
We consider the problem of retrieving multiple documents relevant to the single subtopics of a given web query, termed “full-subtopic retrieval”. To solve this problem we pres...
Andrea Bernardini, Claudio Carpineto, Massimiliano...
ICMCS
2010
IEEE
169views Multimedia» more  ICMCS 2010»
13 years 11 months ago
Comparison of clustering approaches for summarizing large populations of images
This paper compares the efficacy and efficiency of different clustering approaches for selecting a set of exemplar images, to present in the context of a semantic concept. We eval...
Yushi Jing, Michele Covell, Henry A. Rowley
CVPR
2010
IEEE
14 years 6 months ago
Hierarchical Convolutional Sparse Image Decomposition
Building robust low and mid-level image representations, beyond edge primitives, is a long-standing goal in vision. Many existing feature detectors spatially pool edge information...
Matthew Zeiler, Dilip Krishnan, Graham Taylor, Rob...