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CIKM
2006
Springer
13 years 10 months ago
Efficiently clustering transactional data with weighted coverage density
In this paper, we propose a fast, memory-efficient, and scalable clustering algorithm for analyzing transactional data. Our approach has three unique features. First, we use the c...
Hua Yan, Keke Chen, Ling Liu
WEBI
2005
Springer
14 years 2 months ago
Improving Web Clustering by Cluster Selection
Web page clustering is a technology that puts semantically related web pages into groups and is useful for categorizing, organizing, and refining search results. When clustering ...
Daniel Crabtree, Xiaoying Gao, Peter Andreae
SDM
2009
SIAM
225views Data Mining» more  SDM 2009»
14 years 5 months ago
Integrated KL (K-means - Laplacian) Clustering: A New Clustering Approach by Combining Attribute Data and Pairwise Relations.
Most datasets in real applications come in from multiple sources. As a result, we often have attributes information about data objects and various pairwise relations (similarity) ...
Fei Wang, Chris H. Q. Ding, Tao Li
ICCV
2003
IEEE
14 years 10 months ago
Dominant Sets and Hierarchical Clustering
Dominant sets are a new graph-theoretic concept that has proven to be relevant in partitional (flat) clustering as well as image segmentation problems. However, in many computer v...
Massimiliano Pavan, Marcello Pelillo
ICIP
2008
IEEE
14 years 10 months ago
Feature-based object modelling for visual surveillance
This paper introduces a new feature-based technique for implicitly modelling objects in visual surveillance. Previous work has generally employed background subtraction and other ...
Gary Baugh, Anil C. Kokaram