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» Clustering by pattern similarity in large data sets
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DMKD
1997
ACM
198views Data Mining» more  DMKD 1997»
15 years 1 months ago
Clustering Based On Association Rule Hypergraphs
Clustering in data mining is a discovery process that groups a set of data such that the intracluster similarity is maximized and the intercluster similarity is minimized. These d...
Eui-Hong Han, George Karypis, Vipin Kumar, Bamshad...
86
Voted
KDD
2008
ACM
140views Data Mining» more  KDD 2008»
15 years 10 months ago
Semi-supervised approach to rapid and reliable labeling of large data sets
Supervised classification methods have been shown to be very effective for a large number of applications. They require a training data set whose instances are labeled to indicate...
György J. Simon, Vipin Kumar, Zhi-Li Zhang
TKDE
2008
156views more  TKDE 2008»
14 years 9 months ago
A Framework for Mining Sequential Patterns from Spatio-Temporal Event Data Sets
Given a large spatio-temporal database of events, where each event consists of the fields event ID, time, location, and event type, mining spatio-temporal sequential patterns ident...
Yan Huang, Liqin Zhang, Pusheng Zhang
CVPR
2007
IEEE
15 years 11 months ago
Discovery of Collocation Patterns: from Visual Words to Visual Phrases
A visual word lexicon can be constructed by clustering primitive visual features, and a visual object can be described by a set of visual words. Such a "bag-of-words" re...
Junsong Yuan, Ying Wu, Ming Yang
ADMA
2009
Springer
145views Data Mining» more  ADMA 2009»
15 years 4 months ago
A Framework for Multi-Objective Clustering and Its Application to Co-Location Mining
The goal of multi-objective clustering (MOC) is to decompose a dataset into similar groups maximizing multiple objectives in parallel. In this paper, we provide a methodology, arch...
Rachsuda Jiamthapthaksin, Christoph F. Eick, Ricar...