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148
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EDBT
2008
ACM
167views Database» more  EDBT 2008»
16 years 4 months ago
HISSCLU: a hierarchical density-based method for semi-supervised clustering
In situations where class labels are known for a part of the objects, a cluster analysis respecting this information, i.e. semi-supervised clustering, can give insight into the cl...
Christian Böhm, Claudia Plant
163
Voted
GIS
2002
ACM
15 years 4 months ago
Opening the black box: interactive hierarchical clustering for multivariate spatial patterns
Clustering is one of the most important tasks for geographic knowledge discovery. However, existing clustering methods have two severe drawbacks for this purpose. First, spatial c...
Diansheng Guo, Donna Peuquet, Mark Gahegan
JCB
2002
160views more  JCB 2002»
15 years 4 months ago
Inference from Clustering with Application to Gene-Expression Microarrays
There are many algorithms to cluster sample data points based on nearness or a similarity measure. Often the implication is that points in different clusters come from different u...
Edward R. Dougherty, Junior Barrera, Marcel Brun, ...
JCSS
2008
159views more  JCSS 2008»
15 years 4 months ago
Analysing distributed Internet worm attacks using continuous state-space approximation of process algebra models
Internet worms are classically described using SIR models and simulations, to capture the massive dynamics of the system. Here we are able to generate a differential equation-base...
Jeremy T. Bradley, Stephen T. Gilmore, Jane Hillst...
149
Voted
CG
2004
Springer
15 years 4 months ago
A barcode shape descriptor for curve point cloud data
In this paper, we present a complete computational pipeline for extracting a compact shape descriptor for curve point cloud data. Our shape descriptor, called a barcode, is based ...
Anne D. Collins, Afra Zomorodian, Gunnar Carlsson,...