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ICDE
2005
IEEE
132views Database» more  ICDE 2005»
16 years 7 days ago
CLICKS: Mining Subspace Clusters in Categorical Data via K-partite Maximal Cliques
We present a novel algorithm called CLICKS, that finds clusters in categorical datasets based on a search for kpartite maximal cliques. Unlike previous methods, CLICKS mines subs...
Mohammed Javeed Zaki, Markus Peters
WSC
2007
15 years 9 months ago
Predicting cluster tool behavior with slow down factors
Cluster tools are representatives of a special kind of tool where process times of jobs depend on the combination in which they are processed together on the tool and hence, depen...
Robert Unbehaun, Oliver Rose
ICDAR
2009
IEEE
16 years 1 months ago
A Laplacian Method for Video Text Detection
In this paper, we propose an efficient text detection method based on the Laplacian operator. The maximum gradient difference value is computed for each pixel in the Laplacian-fil...
Trung Quy Phan, Palaiahnakote Shivakumara, Chew Li...
160
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CIS
2004
Springer
16 years 21 hour ago
A Method of Acquiring Ontology Information from Web Documents
Abstract. Ontology plays an important role on the Semantic Web. In this paper, we propose a method, AOIWD, of acquiring ontology information from Web documents. The AOIWD method em...
Lixin Han, Guihai Chen, Li Xie
CORR
2008
Springer
158views Education» more  CORR 2008»
15 years 6 months ago
Improved Smoothed Analysis of the k-Means Method
The k-means method is a widely used clustering algorithm. One of its distinguished features is its speed in practice. Its worst-case running-time, however, is exponential, leaving...
Bodo Manthey, Heiko Röglin