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KDD
2003
ACM
99views Data Mining» more  KDD 2003»
15 years 10 months ago
Fragments of order
High-dimensional collections of 0-1 data occur in many applications. The attributes in such data sets are typically considered to be unordered. However, in many cases there is a n...
Aristides Gionis, Teija Kujala, Heikki Mannila
KDD
2003
ACM
191views Data Mining» more  KDD 2003»
15 years 10 months ago
Assessment and pruning of hierarchical model based clustering
The goal of clustering is to identify distinct groups in a dataset. The basic idea of model-based clustering is to approximate the data density by a mixture model, typically a mix...
Jeremy Tantrum, Alejandro Murua, Werner Stuetzle
KDD
2002
ACM
155views Data Mining» more  KDD 2002»
15 years 10 months ago
SyMP: an efficient clustering approach to identify clusters of arbitrary shapes in large data sets
We propose a new clustering algorithm, called SyMP, which is based on synchronization of pulse-coupled oscillators. SyMP represents each data point by an Integrate-and-Fire oscill...
Hichem Frigui
KDD
2002
ACM
170views Data Mining» more  KDD 2002»
15 years 10 months ago
On interactive visualization of high-dimensional data using the hyperbolic plane
: se the concept of visualizing general abstract data by intermediate projection into the hyperbolic space. Its favorable properties were reported earlier and led to the "hype...
Helge Ritter, Jörg A. Walter
KDD
2001
ACM
163views Data Mining» more  KDD 2001»
15 years 10 months ago
Learning to recognize brain specific proteins based on low-level features from on-line prediction servers
During the last decade, the area of bioinformatics has produced an overwhelming amount of data, with the recently published draft of the human genome being the most prominent exam...
Henrik Boström, Joakim Cöster, Lars Aske...