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ICDM
2007
IEEE
179views Data Mining» more  ICDM 2007»
15 years 11 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»
16 years 5 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
16 years 1 days 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»
15 years 6 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
16 years 1 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...